10

 [10]
As an aside and with regard to the exemplary TPO data structure (30T.0), it is to be understood that the here detailed topic primitive object (TPO) is an example of a more generic concept of a machine stored and pre-categorized, cognition-representing primitive object (CRPO). There are a number of choices that system designers can make when implementing a topic space and/or another system-maintained Cognitions-representing Space. The points, nodes or subregions (PNOS's) of the designed space may be free-ranging; meaning that such PNOS's can be freely moved to any desired part of hierarchical and/or spatial space at the users' whims; or in another extreme the PNOS's may be restricted to specific parts of hierarchical and/or spatial space as dictated by system administrators. Between these extremes are various sub-combinations, including the possibility of having cognitive-sense-representing clustering center points that are fixed within hierarchical and/or spatial space or are free-floating or are restricted to specific parts of hierarchical and/or spatial space as dictated by system administrators. In the example given by FIGS. 3Ta-3Tb, the topic nodes are substantially free-ranging (with the possible exceptions noted in FIG. 3S for the root node 30S.59 and the catch-all 30S.55 and the top topic domains 30S.57) and there are no cognitive-sense-representing clustering center points in the exemplary version of system topic space. It is to be understood however, that it is within the contemplation of the present disclosure to alternatively have a topic space that does contain cognitive-sense-representing clustering center points; in which case fields such as 30W.7 b and 30W.7 c of FIG. 3W might also be included in the topic node data structure 30T.0 of here described FIGS. 3Ta-3Tb.
A first field 30T.1 a of the exemplary TPO data structure (30T.0) of FIG. 3Ta includes a link (e.g., pointer data) to the parent node in the universal “A”-Tree if there is such a universal tree. Not all embodiments have to have a hierarchical “A”-Tree. One alternate embodiment has only a universal spatial topic space (an “A” space) in whose coordinate-defined grid all nodes, points or subregions lie and where spatial distance between such points, nodes or subregions indicates how closely or not, they cluster relative to one another. Each point, node or subregion in such a spatial space has a corresponding and unique location (address) by of which it is uniquely addressed. Subregions in this “A” space may also have predefined extents (e.g., a limiting radius extending from a corresponding center point of the spatial subregion). Points, nodes or subregions within the “A” space may point to an encompassing subregion as being their parent or may point to a specific other point or node as being their parent. By contrast, if a universal “A”-Tree is used, Each point, node or subregion (except the root node 30S.59) has a corresponding and unique hierarchical parent node under which it resides and by way of which it can be identified in combination with a unique node name or unique spatial address inside the parent node's branch space.
In view of the above explanation, it may be seen that the first field 30T.1 a of FIG. 3T allows for any permutation using up to three of the illustrated possibilities: (1) uniquely identifying the parent node; (2) identifying unique coordinates for the represented TPO (e.g., node) in a corresponding spatial space and optionally pointing to a position of a parent in that corresponding spatial space (e.g., “A” space); and/or (3) identifying unique coordinates in a corresponding branch space (e.g., 30R.10) of the uniquely identified parent node (e.g., 30R.30). The corresponding spatial space (e.g., “A” space) in which the TPO optionally resides need not be a 3-dimensional one and can instead be of dimensional value greater than one (e.g., a 1.5D space composed of uniquely identifiable lines or curves each having uniquely identifiable points thereon) including spaces with dimensionalities greater than 3. An example of a 2.5D space under this definition is a set of concentric 2D toruses (flat donuts). Although not shown in FIG. 3Ta, there is yet another possibility where the represented TPO is currently not attached to a real parent point, parent node or parent subregion. This can happen for example when the TPO is drifting between anchor points—see for example 30S.53 of FIG. 3S. In such a case the first field 30T.1 a points to a so-called and predefined, null parent; this indicating that there is no real parent at the moment.
A second field 30T.1 b of the exemplary TPO data structure (30T.0) contains the primitive's uniqueness-guarantying stamp. The uniqueness-guarantying stamp 30T.1 b can be an extension of the primary node identification provided by the first field 30T.1 a. More specifically, if the first field 30T.1 a uniquely identifies a corresponding parent node, the unique-making stamp 30T.1 b may simply be a unique serial number (or other code sequence) that uniquely identifies the represented node relative to other children of the parent node. However, since in one embodiment, every topic node (except the root 30S.59 of course, and also the top catch-all (the null-topic topic node) 30S.55 and the top, notnull-topic topic zones node 30S.57) is free to drift to a new parent node and/or to a new spatial location, it is preferable that each created TPO have its own unique serial number/identifier as well as a corresponding one or more version dates stamps.
When a topic primitive object (TPO, e.g., a topic node) breaks away from (or is otherwise removed from) a previous location on the universal “A”-Tree and/or from a previous location within the universal spatial space of the corresponding topics mapping mechanism (a.k.a. topic space) so as to, for example, move to a new location, the breaking away TPO (e.g., 30S.53 of FIG. 3S) leaves behind a short-form, “I was here” marker. The short-form, “I was here” marker consists essentially of the TPO's unique serial number (TPO Ser. No.) and the TPO's version date stamps. A first version date stamp indicates when the TPO originally attached to the “I was here” location (at which it no longer resides). A second version date stamp indicates when the TPO moved away (on its own or was forced to depart) from the “I was here” location.
In addition to the “I was here” tag, there also and optionally can be a “this-TPO-is-dead” versus “this-TPO-is-alive” flag area 30T.1 c which indicates whether or not the corresponding topic primitive object (TPO) is no longer attached to the pointed-to hierarchical parent node and/or to the pointed-to spatial parent location. If the tagged location is one where the TPO no longer resides, the “this-TPO-is-dead/alive” flag area 30T.1 c of that tag will include an explanation of why the TPO is no longer there and perhaps where it next moved to. In one embodiment, system administrators can kill a node if its attached chat rooms are persistently engaging in inappropriate conduct. In that case, the “this-TPO-tag-is-dead” flag 30T.1 c will include an explanation of why the system administrators killed it so that offending users know the reason. The “this-TPO-tag-is-dead” flag area 30T.1 c may further include a link to an appeal site whereat system users might appeal the administrators' decision to kill the now-dead node. In one embodiment, one or more spaces-crawling automated bots crawl through all nodes of topic space (and/or other system-maintained CARSs) and all the chat or other forum participation sessions tethered to them, searching for evidence of inappropriate conduct. If a below threshold amount of inappropriate conduct (e.g., use of language that is predetermined to be inappropriate for that zone) is discovered by the bot, the node and its forums are marked for more frequent return visits and an accumulating score is kept (stored) for each. If the accumulating score crosses a first predetermined threshold, warnings are automatically sent to members of the governance body. If the accumulating score next crosses beyond a second predetermined threshold, the node and/or its cross-associated forums are automatically killed by the bot. Progeny nodes and their associated forums are also killed by this operation. Explanations are emailed or otherwise transmitted automatically to the governance bodies of the killed nodes/forums explaining why the automated kill took place and explaining the procedure for appealing.
In one embodiment, the dead-or-alive flag area 30T.1 c may include a map of (or a pointer to such a map which maps) the remainder of the data structure 30T.0. This included or point to map (not shown) indicates the respective locations in machine memory space of the other fields of the TPO representing data structure 30T.0 and their respective sizes. For example, if the represented TPO does not appear on alternate trees besides the “A”-Tree and/or does not appear in alternate spatial coordinates (B, C, etc.) besides that of the “A”-universal space, then respective fields 30T.2 and 30T.3 may be empty and of minimized size or not there at all. The data structure map (not shown) of flag area 30T.1 c will indicate this and may further indicate the same for others of the fields of data structure 30T.0 and may further indicate how many such fields (e.g., beyond 30T.14, 30T.15 or 30T.16 of FIG. 3Tb) the data structure has. Alternatively such a data structure mapping specification and pointers to it may be recorded in a different area of the system's machine memory space.
In one embodiment, the dead-or-alive flag area 30T.1 c may further provide an over-time fade out function. The over-time fade out function operates as follows. If certain fields (e.g., 30T.13 of FIG. 3Tb) of the TPO data structure are not referenced by users ever, or are not referenced over a prolonged (and predefined) amount of time; and the corresponding TPO is flagged as being an inconsequential node (e.g., not used by any personas of long term importance to the surrounding subregion of topic space), then this information regarding non-use and inconsequentialness is recorded in the dead-or-alive flag area 30T.1 c and eventually an automated background garbage collecting or gardening bot (not shown) crawls by and automatically reorganizes the represented data structure 30T.0 by deleting (trimming away) the unused or not-in-a-long time used and so-identified fields or by deleting substantially all of the TPO data structure save for the “I was here” marker data. In this way, topic nodes that are added to topic space but never thereafter used or not used for a very long time (and not likely to be ever used in the future by system users) can be removed from the system's memory space so that they do not unusefully consume system memory space. In an alternate embodiment, unused or rarely used TPO's can have most of their data structure compressed where a this-node-is compressed tag is added to the dead-or-alive flag area 30T.1 c.
A further field 30T.1 d of the exemplary TPO data structure (30T.0) contains so-called, anchor factors. These indicate how strongly the represented node anchors by itself to its respective location in topic space (see also 30R.61/63 of FIG. 3R) and/or what positive or negative, anchor reinforcing factors it lends to nearby siblings or they to it, and/or what repulsive or attractive (push away/pull closer in) forces it applies to voted-upon nearby siblings and/or what repulsive or attractive (push down and away/pull closer up) forces it applies to voted-upon child nodes of itself. The attract/repel forces may have different strength values and, in one embodiment as described elsewhere herein, color coded lines may be displayed to graphically show to users the presence of such attraction or repulsion forces and their strengths.
If the represented node is dead or moved away, then fields 30T.1 a through 30T.1 c are all that remain of it. The rest of the data structure (30T.0) is not needed and thus, in one embodiment, is not stored or in other embodiment compressed and stored as compressed data. On the other hand, if the represented node is alive and well at its present location, then in addition to the anchor factors field 30T.1 d, it may include a next section 30T.2 filled with sorted pointers (or a pointer to such sorted pointers) pointing to optional other parent nodes on optional other tree structures (beyond the “A”-Tree). In other words, the represented node may have a different parent node or linked-to peer on the “B”-Tree, on the “C”-Tree, and so on. Typically, system users will want to know which of these alternate parent nodes (on the “B”-Tree, etc.) is/are the most recently referenced ones, the hottest ones, the most popular alternate parent node among users of the represented node, which is the one that is most well regarded by only users having high reputation and/or high credentials, etc. There can be many such lists having different ranking categories (with optional sorting per the rankings) and different effective dates or durations. (See also section 30T.12 of FIG. 3Tb as discussed below.) Accordingly, in one embodiment, section 30T.2 indicates how many sorted columns (in area 30T.2 b) there are in each of its one or more tabs and how many tabs there are (in area 30T.2 a). The nature of each sorted column of alternate parents is described by the column header. Typically, the most popular-among-all-users is the first provided list in the first column of the first tab. Each column also indicates (in area 30T.2 c, 2 d, etc.) how many rows it has.
Just as section 30T.2 provides sorted lists of pointers to alternate parent nodes of alternate hierarchical trees, next section 30T.3 provides sorted lists of pointers to alternate locations in the branch spaces of the alternate parent nodes. The sorted lists (e.g., most popular, most reputable) of section 30T.3 correspond on essentially a one-for-one basis with those of previous section 30T.2 and thus further explanation is not needed. If a respective alternate parent node does not have a spatial branch space, the corresponding pointer of section 30T.3 is coded as a null or invalid pointer.
In the hypothetical story above of how node 30S.9 a (of FIG. 3S) came to be born and placed by original users A and B, it was indicated that the two users were deemed as founding fathers of the node. In general, a topic node can have any practical number of founding fathers. Users of the system may wish to know who the founding fathers were, what their respective reputations are or were, and/or other data about the founding fathers. This is particularly true if the users wish to “follow” or track the contributions of certain admired (or despised as the case may be) other personas, including tracing to the original topic nodes that those admired/or-otherwise personas had a hand in creating. A topic node that is a direct child of the root's null-topic node 30S.55 is not considered to be a created topic node because it has no agreed-to topic specification at that stage. However, when the controlling governance body (e.g., users A and B) agree to move the given node off the branch of the root's null-topic node 30S.55 and to someplace else in topic space, those members of the governance body are deemed to be its founding fathers. (The locations to which the moved node goes after is covered by data in the next-described section 30T.5 a.) Like other cases where users can benefit from having pre-sorted lists of information based on popularity among all users, popularity among highly credentialed users and so on, the founding fathers section 30T.4 provides pointers to (or a pointer to such lists of pointers) bibliographic information about the founding fathers (a.k.a. original node authors) where the identifications of the founding fathers are pre-sorted according to who is most popular, who has the highest reputation, and so on.
As indicated at 30T.4 a, the respective bibliographic information about each founding father (which founder may be a virtual persona instead of a real life person) may include a system-provided unique identification number for that persona, public biography information about the identified persona if such information is available, information about publicly available (and optionally certified) credentials of the identified persona (e.g., college degrees, etc.), information about publicly available reputation scores (optionally certified) for that identified persona in different subject matter areas, information about publicly known affiliations (e.g., business groups, scholastic groups, etc.) of the identified persona, and so on. One of the functions that the founding fathers section 30T.4 can serve is to provide attribution to those personas who decided to launch a new topic node when moving their chat or other forum participation session from under the topic catch-all node (a.k.a. null topic node 30S.55) to a new position within topic space, which new position includes the new topic node they create (by naming it, positioning it, etc.). In one embodiment, the STAN—3 system automatically suggests to participants of forums taking place under null topic node 30S.55 the possibility of creating their own new topic node if they can't find a pre-existing one to which their Notes Exchange session belongs and/or the possibility of moving their Notes Exchange session (e.g., online chat) for attachment to (tethering to) one or more pre-existing nodes or subregions in topic space to which their Notes Exchange session appears to belong. The suggestion to create a new topic node may also include mention that the founders will receive attribution for being the founding fathers of the new node. Hence there is incentive for creating new nodes. The suggestion to create a new topic node may also include a pointer to instructions of how to create a new topic node. The Help menu for STAN-spawned forums may also include a pointer to instructions of how to create a new topic node so that participants who are dissatisfied with a current topic node and want to form a new, different node can easily do so.
Some of the information provided in data structure section 30T.4 a may be in the form of a pointer to a system-maintained user-to-user associations (U2U) database 30T.6 b of the STAN—3 system. More specifically, if a first tracked founding father is indicated to be affiliated with a system-tracked group of other system users, the logical link from data structure section 30T.4 a into database 30T.6 b may be further traced back through to identify the other system users (e.g., 30T.6 a) with whom the first founding father is affiliated and to discover the nature of that affiliation. The traced-back-to other persona may also be a founding father or a member of a governance body or of another group (30T.6) associated with the node and hence an otherwise hidden network of connections between the various personas who founded or ruled or currently rule the given node may be uncovered by tracing back through the system-maintained user-to-user associations (U2U) database 30T.6 b. Such a discovery tool for determining who is affiliated with whom cab be particularly valuable in business oriented research where it is desirable to know which hidden other personas are cross affiliated with the node's founding fathers, with the node's current governance body and how.
In one embodiment, a further tool is provided (not shown) for uncovering the currently shared areas of topical or other focus as between two or more of the founding fathers and/or of other personas (e.g., governance body members) cross-associated with them. Therefore, once a system user finds a topic node he/she admires and decides that he/she might want to follow one or more influential persons or groups (e.g., founding fathers, governance body members) and/or follow up on topics of current hot focus by those persons or groups, the tool allows the user to do so.
As indicated at 30T.5 a and 30T.5 b, the exemplary data structure for the represented topic primitive object (TPO) may include pointers to one or more histories regarding the node's migration histories (plural intended). Reasons for why a given node can have plural migration histories are many. First, the node can simultaneously reside on the “A”-Tree, a “B”-Tree, a “C”-Tree, etc. and the node's positionings on each such hierarchical or non-hierarchical tree can vary. Second, a current node can be the result of merger of two or more separate and earlier existing nodes or a splitting of an earlier existing node into plural nodes. Each pre-existing node may have its own pre-merger history of migrations (and the parent node of a split may also have one or more histories). The pointed to histories may include narrative of what happened and when (e.g., what votes were cast by what members of a controlling governance body) to invoke each migratory move and/or bifurcation and/or merger. The various histories may be used to automatically depict a trajectory and optionally also automatically generate a prediction of further migration based on past history. By contrast, section 30T.5 b contains sequential pointers to the locations in hierarchical and/or spatial frames between which migratory moves took place where the sequential pointers are ordered according to the time lines of the migratory moves. This too can be used for mapping the migrations and predicting future moves. It is within the contemplation of the present disclosure to provide an automated tool that can display to a user the migration histories (through a same hierarchical and/or spatial frame) of two or more identified nodes so that the user can see where (and when) the identified nodes were clustered close together and where/when they were spaced relatively far apart. A user may optionally also follow the plural migratory moves of a single node as it drifts within respective ones of the “A”-Tree, “B”-Tree, “C”-Tree, etc. This may help shed light on how and why a particular topic evolved to what it is at present. An automated trending tool may be included within the system's informational resources for predicting where to and when certain topic nodes are expected to next migrate. Such information can be useful to marketing groups who wish to proactively anticipate where certain demographic groups of people are heading in terms of clustering of previously spaced apart topical concepts. (By way of example, assume that the keyword, “neuorplasticity” was previously restricted to the biological sciences quadrant of topic space, but more recently—as a hypothetical—growing clusters of people are drifting respectively controlled nodes with this as one of their top keywords into the cloud computing quadrant of topic space. Such a hypothetical might lead to an evidence supported conclusion that there is growing and snowballing group cognition out there that a cloud computing environment can have a neuorplastic type of innervation structure embedded within it (where the innervation is composed of machine-implemented logical links and the links strengthen or weaken, grow in one direction or recede from another based on how many users fire up those innervations by means of direct or indirect ‘touchings’ on the nodes—i.e. synaptic ends—of those machine-implemented logical links).
Referring to section 30T.6 of FIG. 3Ta (where strip 30T.0 b is an extension of strip 30T.0), each topic node can have one or more forums (e.g., online chat rooms) tethered to it. Some are strongly tethered (anchored) to it because the governance bodies of those forums voted for such clipped-wing semi-permanence (see again 30S.60 of FIG. 3S). Others are forums which are still drifting by (see again 30S.62 of FIG. 3S) because their governance bodies have not voted to settle down in that way and they still searching for perhaps a better topic node to tie their anchor to; where that better topic node might be one that they clone by copying and slightly modifying an existing topic node—that is, by copying data structure 30T.0, modifying it, and submitting it to a make-me-a-new-node tool (not shown) of the STAN—3 system, where, after checking for format correctness, the system can create such a requested new node provided the requesters are appropriately pre-qualified to request such creation. Alternatively or additionally, the node cloning group may modify a plurality of pre-existing nodes, combine fragments of those modified nodes and then submit the new creation to the make-me-a-new-node tool (not shown). Irrespective of that, an important attribute of most topic or other nodes is keeping track of how many and what kinds of chat or other forum participation sessions are currently tethered to that represented node and keeping track of which of those forums have governance privileges for the represented node. This is the function of section 30T.6. It maintains sorted lists (or logical linkages to such lists) of various individuals or groups (e.g., governance bodies, chat room or other online forums) that are tethered to the node in one form or another. In particular, section 30T.6 identifies the one or more governance bodies that are in current control of the represented node where such bodies may be listed according to which one is largest (e.g., most popular), which ones have the greater levels of control over the maintenance of the represented node (e.g., most powerful), which ones have the highest levels of credentials or reputations and so on. The node's governance bodies can vote to determine a large portion of the node's attributes, including but not limited to, where in its Cognitive Attention Receiving Space the node resides (except that push and shove voting may determine fine resolution location within a branch space as was explained for 30R.9 c of FIG. 3R), what the primary name (30T.8, described below) will be for the represented node, what the node's specifications (30T.9, described below) might say, and so on.
Another type of node-associated set of groups or personas that are identified by section 30T.6 are the so-called, stable forums and groups. These are distinguished from node-associated fly-by-night forums/groups. An example of a fly-by-night forum would be a two-person online chat room that temporarily tethers to the represented topic node (TPO) for just a few minutes or hours and then breaks away and then drifts away to tether to a different node. By contrast, other forums; such as node-dedicated blogs and tweets whose communications are generally dedicated to that specific one and represented node would be tethered basically for their lives to the represented node (married to that node) and thus such would be the most stably attached to that node. In the spectrum between fly-by-night forums or groups and married-to-the-node forums/group there can be all variations of attachment to the represented node including for example forums or groups that are tethered on a 50/50% basis to the represented node and also to another such node. As may be apparent at this stage, node-associated forums can include chat rooms, blogs, live video conferences and the like. Node-associated other “groups” however, are not necessarily engaged in communicative discourse with one another, but rather they remain cross-associated to the one represented node nonetheless. An example would be a group of so-called, “experts” (30T.6 e) who basically leave their virtual calling or virtual business cards attached to the given node so that people who want to contact them with regard to the specific topic or another attribute of the represented node can do so. The pointers of “experts” subsection 30T.6 e may point to corresponding records in the user-to-user associations (U2U) database 30T.6 b.
In one embodiment, the pre-sorted pointers of section 30T.6 each point to a corresponding record 30T.6 a in the system's user-to-user associations (U2U) database 30T.6 b. Accordingly, just as a trace back may be carried out from a given founding father's record 30T.4 a and by way of his/her public affiliations fields to other users or groups identified within the U2U database 30T.6 b, the public record 30T.6 a of almost any forum, persona or other type of group listed in the tethered persons/groups/forums section 30T.6 can be consulted by system users to trace forward through its public affiliations fields to yet other users or groups identified within the U2U database 30T.6 b.
Although in theory an almost unlimited number of node-associated groups, personas and forums could be point to by section 30T.6, such is not practical. Instead the provided lists are limited to a pre-specified top Nk such entities where Nk may vary as a function of the kth set of groups, personas or forums being considered. More specifically, Nk for the k value associated with most stable node-associated forums might be set to 100 while Nk for the k value associated with least stable of recent fly-by-night entities that most recently tethered to the represented node might be set to 5 (as an example). In terms of visualization, the represented node may be likened to a planet having different orbital shells as well as a terra firma surface. Entities that marry/dedicate themselves essentially for life to that planet (e.g., the node's primary governance body) can be visualized as being rooted to the planet's surface. On the other hand, fly-by-night chat rooms that temporarily pop into orbit around that node and then move on a short time later can be visualized as being temporarily parked in the outermost orbit. Other entities in the spectrum between those extremes can be visualized as parking themselves in lower planetary orbits. Section 30T.6 can be visualized as a sort of census bureau that keeps track of the more prominent citizens and visitors but not necessarily of everyone.
When a system user, or even an automated bot that is crawling through a given sector of topic space, comes upon a node (e.g., the represented TPO) that he/it is not yet familiar with, he/it may wish to know; even before exploring deeper, what kind of node is being encountered based on evaluations provided by earlier visitors and/or by inhabitants of neighboring nodes. Therefore and in accordance with one aspect of the present disclosure, a ratings and warnings section 30T.7 is provided as part of the TPO data structure 30T.0 where this section 30T.7 may contain sorted lists of (or pointers to such lists of) ratings given by rating providing organizations or services to the node and/or warnings posted by such organizations or services or previous visitors regarding the nature of the node. More specifically and by way of example, an included warnings subsection 30T.7 a may provide warnings that indicate the node and its children (if any) are intended for mature audiences only (no minors) and/or that the forums associated with the node or the informational other resources provided by the node might be viewed as offensive to some persons where the potentially offensive material pertains to politics and/or religion and/or ethnicity and so on. Therefore, and as an example, an automated search bot (see 30T.11 b) that is crawling through that area of topic space on behalf of a minor user (e.g., Fifth Grade Student), stops crawling down that branch and subbranches of topic space when it encounters warning signs (30T.7 a) indicating the material is inappropriate. Accordingly time is saved and persons for whom the material is deemed inappropriate may be blocked from seeing it.
With regard to the illustrated ratings subsection 30T.7 b, one of the stored ratings may be based on where in a parent node's branch space (e.g., 30R.10) the represented node resides and what attractive or repulsive clustering scores are given to that node from the parent node and/or from neighboring sibling nodes. As may be recalled from the discussion of FIG. 3R, the placement of a child node within its parent's branch space (e.g., 30R.10) may be a function of repulsion and attraction forces applied to that given node from governance bodies of the parent node (e.g., 30R.30) and/or of neighboring sibling nodes. Therefore, the STAN—3 system can automatically generate some of the ratings of subsection 30T.7 b simply based on how the corresponding parent and sibling nodes (more specifically, the governance bodies of those other nodes) rate the given node (e.g., 30R.9 c).
Referring to section 30T.8 of FIG. 3Ta, each topic node (TPO) may be assigned a primary name and one or more alias names by respective governance bodies and/or user groups. Section 30T.8 may contain sorted lists of (or pointers to such lists of) primary and alias names, where the lists are sorted according to popularity of the naming entity, credentials of the naming entity and so on.
Referring to section 30T.9 of FIG. 3Ta, each topic node (TPO) may have one or more topic specifications attached to it for explaining; from the perspective of the author of that specification, what the topic is about. The one or more specifications may be written by or otherwise provided by a respective governance body and/or by a respective one or more user groups associated with that topic node. Unlike the well known Wikipedia™ web site where for a given term there is usually one and only one definition of that term, in accordance with the present disclosure, many alternative specifications (e.g., different cognitive sensibilities) may be provided for what the topic is “about” as seen through the eyes of the many, perhaps divergent, users of that topic node. Accordingly, section 30T.9 may contain sorted lists of (or pointers to such lists of) specifications, where the lists are sorted according to popularity of the specification-providing entity, credentials of the specification-providing/authoring entity and so on.
Referring to section 30T.10 of FIG. 3Ta, each topic node (TPO) will typically have a so-called, branch space containing the children (progeny nodes) of the represented node where the branch space may be organized as a specific kind of 3-dimensional space (e.g., a solid cylindrical branch space like 30S.10 of FIG. 3S, or a conical space like 30S.40, or other as explained earlier above).
In some cases, it may be of value to list the more popular or otherwise classified child nodes of the represented TPO and/or their locations within the specified branch space. Such sorted lists of (or pointers to such lists of) classified child nodes and their locations may further be provided in section 30T.10. An example use of this prestored and presorted information would be for an automated search bot that is looking to find the most popular top 5 child nodes of the given parent or the 7 most well credentialed or highest reputed child nodes of the given parent. A background service of the STAN—3 system repeatedly tests the branch space of each parent node to determine which children are currently the most popular, the most reputable, etc. and then it updates the information stored in section 30T.10. Therefore when a user's private search bot later comes through looking for such information, it is already there.
Referring to section 30T.11 of FIG. 3Ta, often a topic node is identified based on its top 2-5 keywords or top clusters of keywords or top clusters of context-plus-keyword hybrid expressions. As was explained above for FIG. 3E, keyword expressions and/or hybrid keyword plus context operator nodes may logically link to respective nodes in topic space and the pointed-to topic nodes may reflectively point back (see 370.6, 390.6 of FIG. 3E) to the source keyword space (or source URL space, or source other space as the case may be including source hybrid space point). Section 30T.11 provides such a reflective point back function. An example point, node (e.g., operator node) or subregion in the point to external space (e.g., keyword space) is illustrated at 30T.11 a. Among the external space and reflectively pointed back to points, nodes or subregions; some may be more popular for users of the represented TPO, some may be more preferred by a highly credentialed (e.g., expert) subclass of the users of the represented TPO, some may be the most recently referenced ones and so on. Section 30T.11 may contain sorted lists of (or pointers to such lists of) most popular or otherwise so-sorted and thus classified ones of the reflectively pointed back to points, nodes or subregions in the external spaces. An automated background service of the STAN—3 system repeatedly tests the reflectively pointed back to points, nodes or subregions as listed in section 30T.11 of FIG. 3Ta to determine which are currently the most popular, the most preferred among reputable users, etc. and then it updates the sorted information stored in section 30T.11. Therefore when a user's private search bot 30T.11 b later comes through looking for such information, it is already there. In the case of the illustrated search bot 30T.11 b, item 30T.11 si represents search instructions that have been provided to the bot and that the bot is searching in accordance with. The combination of the executing bot thread and its machine-readable and stored search instructions is denoted as 30T.11 c.
Referring to section 30T.12 of FIG. 3Tb, this a continuation strip 30T.0 c of the exemplary TPO data structure 30T.0 where parts of one embodiment are shown in greater detail in FIG. 3Tb. Various points, nodes or subregions (PNOS's) in various ones of the other system-maintained spaces may be reflectively linked-to from the TPO data structure. Some of those external PNOS's may be inside the system-maintained URL's space (see 390 of FIG. 3E) and section 30T.12 may contain pre-ranked and optionally sorted lists of (or pointers to such lists of) pointers to those parts of URL's space where the lists are ranked and optionally sorted according to different ranking and sorting algorithms (e.g., different ranking categories) and for different effective dates or effective time durations and/or according to different filtering criteria. The pointers that point-to the ranked/optionally-sorted/optionally-filtered lists of external PNOS's (e.g., of URL's space) may be organized in a spreadsheet manner or in other database fashion, where in one embodiment, the pointers (e.g., 30T.12 h) are listed in sorted order in respective columns of tab areas of system memory space and where each tab area has a respective tab number (30T.12T and optionally includes tab update time stamps or tab effective time duration specifications—not shown). Each column has a column number and an associated column title 30T.12 e as well as a column update time stamp 30T.12 f indicating when the respective column's list was last updated and also optionally indicating what set of dates and/or times the ranked/sorted list is for. A zero-ith pointer 30T.12 g in each column may point to a more detailed explanation of what the often-abbreviated column title (30T.12 e) means. In one embodiment, users can view the TPO data structure, including its tabbed lists (e.g., 30T.12 h) in a user friendly format and they can click or otherwise activate the zero-ith pointer 30T.12 f to thereby view the detailed explanation and to thus learn more about what the respective column is showing (e.g., what machine-implemented sorting algorithm was used, what effective dates and times the list covers, what geographic or other filtering criteria may have been used in creating or updating the list, and so on.)
Examples of possible column titles are shown by blocks 30T.12 e 1 through 30T.12 e 8. The corresponding columns may include a first one (30T.12 e 1) listing a most recent subset of new URL's (or URL expressions) that were not listed elsewhere in section 30T.12 and are thus currently new within section 30T.12, where the period for recentness may be a predetermined value N1, for example, in the last 5 minutes (and the column update time 30T.12 f indicates when the 5 minute period ended). A different spreadsheet tab may store similar information for an earlier 5 minutes and so on. This allows for quick calculations of trending changes or persistences (for example indicating that a given new URL has been persistently mentioned for the last hour in each 5 minute subsection of that hour).
A second exemplary column (30T.12 e 2) may provide a listing of pointers pointing to most recent external space PNOS's (e.g., in URL's space) that are new to section 30T.12 over the last N2b minutes (where N2b is a pre-specified number) and that were referenced within one of the top N2a “expert” forums (or by TPO-associated expert groups (30T.6 e) even though those are not currently engaged in an online notes exchange), where these top N2a “expert” forums are currently strongly tethered to the represented TPO or are otherwise cross-associated to the represented TPO (topic primitive object), and where N2a is a pre-specified number.
A third exemplary column (30T.12 e 3) may provide a listing of pointers that are pointing to most recent external space PNOS's that are new to section 30T.12 over the last N3b minutes and that were referenced within one of the top N3a “most reputable” forums (or TPO-associated reputable groups) that are currently strongly tethered to the represented TPO or otherwise cross-associated to the represented TPO. A fourth exemplary column (30T.12 e 4) may do the same for the top N4a “hottest” forums or groups (where the definition of hotness can vary and will be given in the detailed specification pointed to by pointer 30T.12 g).
A fifth exemplary column (30T.12 e 5) may provide a listing of pointers that are pointing to the “hottest” N5a external space PNOS's that were referenced within one of the top N5b “hottest” forums (or hottest TPO-associated reputable groups) that are currently tethered to the represented TPO or otherwise cross-associated to the represented TPO, where there is not necessarily a time limit or effective time span associated to this category.
A sixth exemplary column (30T.12 e 6) is shown generically to provide a listing of pointers that are pointing to the top N6a “other” external space PNOS's that were referenced within one of the top N6b “otherwise categorized” forums (or “otherwise categorized” TPO-associated groups) that are currently tethered to the represented TPO or are otherwise cross-associated to the represented TPO where there is not necessarily a time limit or time span associated to this category, but if there is it is denoted generically as “when” in the generic example of block 30T.12 e 6.
Block 30T.12 e 7 shows an example that was already shown for earlier sections of the TPO data structure, namely, providing a listing of pointers that are pointing to the top N7a most popular URL's (or URL expressions) as referenced by any of the forums currently tethered to the represented TPO or are otherwise cross-associated to the represented TPO where N7a is a predetermined number. Similar additional blocks may provide pointers to a top N7c URL's ever recommended by the most reputable N7d users in any of the forums currently tethered to the represented TPO or are otherwise cross-associated to the represented TPO, and so on.
In general, and if not otherwise specifically stated herein, heat or other attention giving energies cast onto respective points, nodes or subregions of corresponding Cognitive Attention Receiving Spaces (CARS's) can be assumed to be of a positive or “I like this” kind. However, it is within the contemplation of the present disclosure to also indicate when attention giving energies cast onto respective points, nodes or subregions are of a negative or “I especially do not like/despise this” kind. In other words, just as certain URL expressions (or other ranked/rated cognition representing codes) can be rated by users as being the top N7a most popular (most liked, most used) such cognition representing codes and the ranked codes can be optionally pre-sorted according to their comparative rankings; other certain URL expressions (or other ranked/rated cognition representing codes) can be rated by users as being the top N8a most hated, most despised or otherwise negatively thought about representations of corresponding cognitions, where the pointers to the respectively despised cognition representations may be pre-sorted according to their comparative rankings so that the most despised one is listed first for example. Block 30T.12 e 8 shows an example (a non-limiting example), namely, one providing a listing of pointers that are pointing to the top N8a most hated or despised by users of this topic primitive object (TPO 30T.0) among URL's (or URL expressions) as referenced by any of the forums currently tethered to the represented TPO or are otherwise cross-associated to the represented TPO where N8a is a predetermined number and degree of hatred (or despising) is based on number of users voting negatively by implicit or explicit means with regard to connecting the hated URL expression with the represented TPO. Similar additional blocks may provide pointers to a top N8b URL's most despised ever by the most reputable N8c users in any of the forums currently tethered to the represented TPO or are otherwise cross-associated to the represented TPO, and so on.
Although not shown in expanded form, next section 30T.13 may do the same thing for ERL's (Exclusive Resource Locators, i.e. private subscription databases) of a system-maintained ERL space where those identified ERL's are cross-correlated with the represented TPO of FIGS. 30Ta-3Tb.
Similarly, next sections 30T.14 and 30T.15 may respectively do the same thing in positive affirmation sense or negative despising sense for points, nodes or subregions in a system-maintained context space (e.g., 316? of FIG. 3D) or in a system-maintained and hybrid context-plus-other space (e.g., 30S.5 of FIG. 3S) or for yet other (PNOS's) in system-maintained other Cognitive Attention Receiving Spaces. Additionally, and as indicated by next sections 30T.16 and 30T.17, further sorted lists may be provided for other node-related informational resources. These node-related other informational resources (30T.16-17) may include identifiers of topic related educational courses, topic related conferences or other such events, topic related hardware and/or software resources (see university owned resources 190 p.6 of FIG. 1J), topic-related promotional offerings (see 104 a of FIG. 1A), and so on. As mentioned above, in one variation, the further fields (e.g., 30T.17) of the illustrated topic primitive object (TPO) may provide pointers to nearby cognitive-sense-representing clustering center points in topic space if such are used. The further fields (e.g., 30T.17) may alternatively or additionally provide pointers to other nodes in topic space that have substantially same topic prime names (see 30T.8) and/or substantially same topic specifications (see 30T.9) but nonetheless, different cognitive senses for the alike named topic nodes. The latter pointers may define a linked list of same or alike named topic nodes where the pointers also provide indications of ranking that indicate which of the different senses for the same topic node name are more popular and which are less popular. The linked list may be traced through to identify, for example, other topic nodes that have a same or alike name as that of a first identified topic node but are more popular among system users.
Referring next to FIG. 3U as well as to above discussed FIG. 3D, the machine-implemented and automated operations of the CFi categorizing, clustering and inferencing engines 310? may be supported by the illustrated data structure 30U.0 which is also referred to herein as a CFi's Sorting and Reorganizing Object (CFiSRO) or alternatively as a CFi's collecting node 30U.0. As an aside, when people receive language-mediated codings, e.g., words organized as sentences; they often syntactically disambiguate the codings on a subconscious level (give it more of a cognitive sense than warranted by the coding taken alone) by perhaps checking different permutations for sanity ad/or appropriateness to surrounding context. Some permutations will not make any cognition sense or little of it in the surrounding context while others may make much more “sense”. The machine counterpart to that kind of activity may be referred to as involving a Cognition-Representing Objects Organizing Space (a.k.a. CROOS) rather than a Cognitive Attention Receiving Space (a.k.a. CARS) because conscious attention is often not cast on such activities. The illustrated CFi's collecting node 30U.0 resides in a system-maintained and system-organized CROOS. As a second aside, It is to be understood that that the trial-and-error “clustering” of received CFi's is not be deemed as an identical process to the elsewhere described “clustering” of keywords or the like in keyword space and/or in other Cognitions-representing Spaces.
Current focus indicators (CFi's) may come in many different “types”, and when received as packet-packaged data (see packet 30U.10) at the SS3 core portion of the system, the payload CFi data (see field 30U.10 g of packet 30U.10) may have to be reformatted and then matched up with other reformatted (e.g., normalized) CFi data received at other times and/or from different CFi sourcing machines so that CFi's which should be clustered together can be identified (because the clustering thereof makes a system-recognized “cognitive sense” of one kind or another) and clustered together. A simple example of three CFi's that have been cross-correlated to one another and then formed into a CFi's cluster is seen under a first illustrated cluster holder data object 30U.12, where the three CFi's are denoted as CFi#1, CFi#2 and CFi#3. The fact that the one cluster holder data object 30U.12 points to them means that they are clustered together at least temporarily on a trial basis. As explained above, trial clusters of CFi's are formed and trial clusters of clusters (see 30U.14) are formed and these trial basis clusters are subjected to so-called, sanity checks to thereby determine on an artificial intelligence basis if they make sense in view of surrounding contexts.
One method for automatically clustering CFi's includes clustering likes with likes. In other words, a first received CFi that represents a particular smell or chemical vapor is logically linked with a second received CFi that represents a particular smell or chemical vapor if the two were transmitted at roughly the same time (per their time stamps 30U.10 b) and from roughly the same place (per their respective place of origin stamps 30U.10 c as provided by the transmitting packet). Normally, a received CFi that represents a particular smell would not be paired up with a received CFi that represents a particular sound, for example because for most normal cognitions, smells belong with other smells and sounds belong with other sounds of same place of origin and roughly same time of origination. In view of this, when primitive level clustering is being undertaken with aid of a CFi's Sorting and Reorganizing Object (CFiSRO) 30U.0, a CFi's typing specification is provided inside a first section 30U.1 of the CFiSRO data object to specify the type or limited types of CFi's that are to be clustered together under the umbrella of the given CFiSRO.
More specifically, the CFi's collecting node 30U.0 may specify in its first section 30U.1 that it is collecting only smell type CFi's or only emotion representing CFi's or only textual types of CFi's (e.g., only keywords). With that said, it is within the contemplation of the present disclosure that non-primitive or higher cognition level collecting nodes (e.g., those that cluster together clusters of clusters of primitive CFi's collecting nodes like 30U.0) might mix and match cognition representations of different types, for example, a musical sequence and a set of emotions that go together (for whatever reason) with that musical sequence. An example could be marching music mixed with a heart pounding biological state that often comes with that music (i.e. a national anthem) and emotional states that follow as a consequence. Among the different types of CFi's that first section 30U.1 might specify, there could be (but this is not limited to just these), CFi's representing sights, sounds, smells, tastes, different kinds of touch sensations, different kinds of kinesthetic sensations, different kinds of emotional or biological state sensations, textual cognitions (e.g., including keywords, URL's, meta-tags etc.), physical context representations (e.g., specification of surrounding environment, i.e. at work, at home, etc.) and hybrid cognitions including those that mix sensed physical context (XP) with one of the other types of CFi's (e.g., keywords, URL's, etc.).
Aside from trying to cluster likes with likes in terms of type when creating trial clusters of individually received CFi's, the first section may also specify that similarly sized ones of same types of CFi's should be clustered together. More specifically, short textual sequences of some types may be more likely to belong together with other short textual sequences rather than with proportionally much larger/longer sequences. For example a first CFi representing a single word or short phrase is unlikely to belong together with a second CFi representing a full chapter out of a book although a third CFi also representing a full chapter might. So first section 30U.1 may specify size limitations or ranges for the highest level of clusters of clusters that it will hold. (More detailed cluster size ranges are provided in a later described section 30U.3 b.) The size specification in first section 30U.1 tells the system memory management software what rough size of data objects it is dealing with.
When the types and generalized broad sizes of the to-be collected CFi data objects are specified in first section 30U.1, it is often the case that a corresponding inferencing engine (see 310? of FIG. 3D) which is using the specific collecting node 30U.0 will already have one or more predetermined ones of plural Cognition SubTypes of Categorizations already cross-associated (on a trial basis) with the to-be-clustered together set of CFi's it is trying to cluster together. In one embodiment, the number of such predetermined subtypes is stored in list size area 30U.2 n. More specifically, some collected CFi's (say keywords) might be categorized as being of a “sub-type” that is cross-associated with a Limbic Focal Subspace 30U.2 a maintained by the system. By this it is meant that the to-be-clustered together (on a trial basis) CFi's of this pre-subtyped CFiSRO 30U.0 are predetermined (on a trial basis, a hypothesizing basis) to be strongly cross-correlated with a social dynamics cognition area. The latter is an example of a limbic subtype of cognition that could involve social dynamic interactions with other people. If this is the case, the corresponding inferencing engine (see 310? of FIG. 3D) that is working together with the so conjecturally sub-typed CFiSRO 30U.0 when trying to build up a clustering of CFi's will look for permutations that match up with a limbic proposal such as “Gee, can't we all just get along?”. (See FIG. 1M.). At the same time, the same inferencing engine or another one will be trying out a different conjectured subtype for the same set of recently received CFi's and being clustered together CFi's; such as for example, a neo-cortical proposal (example: “This is a scientifically supported theory, not an appeal to emotions”). One of those conjectured subtypes will usually receive a high sanity check score (see 30U.2 e) while the other gets a lower sanity score. With each subtype, there will be a preference for organizing the received CFi's according to a different permutation (e.g., under cluster holder 30U.12).
Some subtypes will receive relatively high scores for sanity check (when so checked) while others will receive relatively lower scores. Due to section limitations in the drawing, only one sanity-score storing area 30U.2 e corresponding to subtype 30U.2 d is shown. However, it is to be understood that each subtype (30U.2 a, 30U.2 b etc.) will have a respective sanity-score storing area like 30U.2 e logically linked with it. The trial-wise tested subtypes that score highest (and are ranked as such) will be pursued more so by the corresponding inferencing engine (see 310? of FIG. 3D) so as to build clusters of clusters (for example) while those subtypes that score low during the first round of trial basis attempts will be ranked lowest and in essence shuffled to the back of a task priority queue, probably to be abandoned if the other trial basis subtypes ahead of them on the queue continue to return highest scores for each round of sanity check (for clusters of clusters and for clusters of those, etc.). In other words, among the possible subtypes: 30U.2 a (limbic subtype), 30U.2 b (neo-cortical subtype), 30U.2 c (survival, reptilian like subtype), 30U.2 d (time and/or spatial coordinates cognition subtype), 30U.2 f (Left-brained cognition subtype or Right-brained cognition subtype0, 30U.2 g (cognition involving multiple topics that cross-correlated in topic space), and so on; there will be a corresponding sanity check score such as the one stored in score holding area 30U.2 e. One of those scores will usually be highest, a second will be next highest and so on. The pointers that point to the subtypes that have highest ones of corresponding sanity check scores (e.g., 30U.2 e) are next ranked as having highest probability of being correct while those with corresponding lowest sanity check scores, as least probable. In response to this, the respective inferencing engine (see 310? of FIG. 3D) focuses its resources (i.e. data processing bandwidth) on testing out CFi's clustering permutations matching the subtype having the highest first round sanity score, and then the one having the next highest and so on. With each round of sanity checking and higher level of clustering (forming clusters of clusters), the pointers are re-ranked based on respective sanity check scores. At the end of the process, the ranked (and optionally sorted) list of pointers 30U.2 will be pointing to a subtype that has the highest sanity check score (e.g., 30U.2 e) corresponding to whatever clusters of clusters permutation (see 30U.14) has been built up under the auspices of the corresponding CFi's collecting node 30U.0. Therefore, when a clusters of clusters is formed under a respective CFi's collecting node 30U.0, section 30U.2 of that collecting node will indicate which subtype (e.g., 30U.2 a-2 g, etc.) is most likely to correspond with the formed complex (e.g., 30U.14) of clustered CFi's.
Referring to section 30U.3 a of FIG. 3U (control codes), the received CFi packets (e.g., 30U.10) can come in with roughly same time-of-origination stamps (30U.10 b) and roughly same place-of-origination stamps (30U.10 c) but from different machines of origin (30U.10 d). The different machines of origin can differently code their respective CFi payloads (30U.10 g) because they use respective and different sets of control codings and different data formats. It is difficult to work with (when clustering the following for example,) CFi payloads (30U.10 g) having different sets of control codings and different data formats. Accordingly, a normative set of control codes and a normative data format should be chosen. Then, all raw CFi payloads (30U.10 g) that are received as having non-normative control codes and non-normative data formats are automatically converted into the normative format that uses the normative set of control codes (e.g., meta codes and meta format). Section 30U.3 a of the collecting node data structure 30U.0 stores the definitions of the normative format and the normative set of control codes. A data format normalizing module (not shown) uses the information in section 30U.3 a to determine if and how to normalize incoming raw CFi payload data (30U.10 g).
Referring to section 30U.3 b, it is often the case that raw CFi data packets (e.g., 30U.10) keep streaming in on a non-stop basis from a monitored system user (identified in portion 30U.10 a of each received packet) as the user moves to different locations over different spans of time. The clusters building process cannot build clusters of infinite size and then make sense of them. A limit has to be set as to how many payloads of a given type (and/or subtype) will be collected under the auspices of a single collecting node 30U.0 for a respective time span and/or for a respective geographic area. Section 30U.3 b stores data for placing a limit on the number of payloads to be processed for each type (and optionally each subtype) of cognition and for respective time spans of origination, locations of origination and so on. A more specific example is shown at 30U.3 c? (extending from magnifier of 30U.14). In the example, the desired span of origination time spans for level one CFi's is between 10 and 30 seconds. In other words, a continuous stream of CFi's that covers an origination span of less than about 10 seconds is rejected and a continuous stream of CFi's that covers an origination span greater than about seconds is rejected for forming a level one cluster under this collecting node 30U.0. (The rejected continuous stream may nonetheless collect under another collecting node 30U.0 having a different setting in its section 30U.3 c?.) The geographic distance between data collecting locations (30U.10 c) may also be delimited in settings section 30U.3 c?, for example having to be in the range 5 to 50 feet. The size of each payload may also be delimited in settings section 30U.3 c?, for example having to be in the range 7 to 80 bytes. For a level 2 clusters of clusters (see 30U.14) the time span of origination can be different than that of the level one clusters, for example 18 to 180 seconds. This can happen because one level one cluster (30U.12) can belong to a first half while a second level one cluster (30U.13) can belong to a second half of the longer span length.
More specifically under this example, a first trial cluster holder 30U.12 may be limited to collecting no more than three CFi's (#1, #2, #3) but no less than two under its auspices. A second trial cluster holder 30U.13 may be limited to collecting no more than five CFi's (#4, #5, #6) but no less than three under its auspices. At the same time, the corresponding level two trial cluster holder 30U.14 (which forms a clusters of clusters) may be limited to collecting no more than 32 CFi's under its auspices but no less than six CFi's (namely, the illustrated CFi's #1, #2, #3, #4, #5, #6). In FIG. 3U, each level one cluster holder (e.g., 30U.12) contains a first set of pointers (e.g., 30U.12 a, 30U.12 b, 30U.12 c) pointing to corresponding ones of received CFi's (e.g., #1, #2, #3) and a second pointer (30U.12 d) pointing to corresponding trial points, nodes or subregions (30U.22) in respective ones of system-maintained Cognitive Attention Receiving Spaces that currently cross-correlate strongly with the clustered collection of received CFi's (e.g., #1, #2, #3). This is in terms of a trial and error basis. The CFi's collecting under the first trial cluster holder 30U.12 can change if a current collection and/or permutation receives a poor sanity check score. Similarly, another level one cluster holder (e.g., 30U.13) contains a respective first set of pointers (e.g., 30U.13 a, 30U.13 b, 30U.13 c) pointing to its corresponding ones of received CFi's (e.g., #4, #5, #6) and a respective second pointer (30U.13 d not shown) pointing to its corresponding trial points, nodes or subregions (not shown) in respective ones of system-maintained Cognitive Attention Receiving Spaces that currently cross-correlate strongly with the clustered collection of received CFi's (e.g., #4, #5, #6). The level one PNOS's set (30U.22 and its level one counterpart (not shown) for CFi's #4, #5, #6) should substantially match. Otherwise it might be that CFi's #4, #5, #6 do not reasonably cross-correlate with CFi's #1, #2, #3. The PNOS's set shown at 30U.24 belongs to pointer 30U.14 d of the level 2 collecting node 30U.14.