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In one embodiment, the handheld device 199 of FIG. 2 further includes an odor or smells sensor 226 for detecting surrounding odors or in-air chemicals and thus determining user context based on such detections. For example, if the user is in a quite meadow surrounded by nice smelling flowers (whose scents 227 of FIG. 2) are detected, that may indicate one kind of context. If the user is in a smoke filled room, that may indicate a different likely kind of context.
Given presence of the various sensors described for example immediately above, in one embodiment, the STAN—3 system 410 automatically compares the more usual physiological parameters of the user (as recorded in corresponding profile records of the user) versus his/her currently sensed physiological parameters and the system automatically alerts the user and/or other entities the user has given permission for (e.g., the user's primary health provider) with regard to likely deterioration of health of the user and/or with regard to out-of-matching biometric ranges of the user. In the latter case, detection of out-of-matching biometric range physiological attributes for the holder of the interface device being used to network with the STAN—3 system 410 may be indicative of the device having been stolen by a stranger (whose voice patterns for example do not match the normal ones of the legitimate user) or indicative of a stranger trying to spoof as if he/she were the registered STAN user when in fact they are not, whereby proper authorities might be alerted to the possibility that unauthorized entities appear to be trying to access user information and/or alter user profiles. In the case of the former (e.g., changed health or other alike conditions, even if the user is not aware of the same), in one embodiment, the STAN—3 system 410 automatically activates user profiles associated with the changed health or other alike conditions, even if the user is not aware of the same, so that corresponding subregions of topic space and the like can be appropriately activated in response to user inputs under the changed health or other alike conditions.
Although in the exemplary cases of FIG. 2, FIG. 1A, etc., the situation is given as one where the user possesses a hand-carryable mobile data processing device such as a tablet computer or a smartphone with a touch responsive screen, it is within the contemplation of the present disclosure to have a user enter an instrumented room, an instrumented vehicle (e.g., car) or other such instrumented area, which area is instrumented with audio visual display resources and/or other user interface resources (IR band detectors, user biological state detectors, etc.) with the user having essentially no noticeable device in hand and to have the instrumented area automatically recognize the user and his/her identity, automatically log the user into his/her STAN_system account, automatically present the user with one or more of the STAN_system generated presentations described herein (where for example, an on-wall screen displays of any one or more of the presentations of FIGS. 1A-1N and 2) and automatically respond to user voice and/or gesture commands. The user may alternatively carry or wear minimalist types of interface devices for interfacing with the instrumented area, such as but not limited to, a worn RFID and/or IR wavelengths band identification device for allowing automated identification and locating of the user, a specially instrumented wrist watch and/or instrumented forearm bands, gloves, and/or instrumented leg bands, socks, shoes, undergarments and/or an instrumented head band/hat and/or special finger rings or other jewelry which are themselves instrumented with one or more of: biological state detectors for facilitating detection of biological states of the user (e.g., heart rate, respiration rate, perspiration rate, other excretions & rates thereof, muscle actuations), position and/or motion detectors for facilitating detection of positions and/or motions of corresponding body parts of the user, and/or communicative subparts for facilitating communicative interfacing as between the user and the instrumented area. If the user is seated or otherwise resting against a seat or like apparatus, the sitting/resting posture facilitating device may be instrumented with one or more interface facilitating means as well for facilitating operative coupling as between the user and the STAN—3 system. Accordingly, a fully equipped smartphone or laptop or tablet computer is not necessarily needed for the user to make more extensive use of the resources of the STAN—3 system. The user may instead enter a STAN-compatible instrumented area (e.g., a live video conferencing support station) and may use the resources available within that are for interacting with the STAN—3 system and/or with other system users by way of the instrumented area and its operative coupling to the core (e.g., cloud portion) of the STAN—3 system. (In one embodiment, if the user's heart rate and respiration are detected to undergo a sudden and substantially large increase, the STAN—3 system automatically deems that to be a medical or other emergency situation and it automatically copies the then developing CFi signals to an Emergency-Management Cognitive Attention Receiving Space. The latter space may include links to medical emergency handling services and/or security breach emergency handling services where the latter can respond to CFi signals received from the user during an apparent exigent circumstance.)
Referring next to FIG. 3A, shown is a first environment 300A where a user 301A of the STAN—3 system is at times supplying into a local data processing device 299, first signals 302 indicative of energetic output expressions Eo (t, x, f, {TS, XS, . . . , OS}) of the user (one form of attention giving energies), where here, Eo denotes energetic output expressions having at least a time t parameter associated therewith and optionally having other parameters associated therewith such as but not limited to, x: physical location (and optionally v: for velocity and a: for acceleration); f: distribution of energy or power over a frequency domain (frequency spectrum); Ts: associated nodes or regions in topic space; Xs: associated nodes or regions in a system maintained context space; Cs: associated points or regions in an available-to-user content space; EmoS: associated points or regions in an available-to-user emotional and behavioral states space; Ss: associated points or regions in an available-to-user social dynamics space; and so on; where the latter is represented by OS, other system-maintained Cognitive Attention Receiving Spaces. (See also and briefly the lower half of FIG. 3D and the organization of exemplary keywords space 370 in FIG. 3E). The illustrated local data processing device 299 of FIG. 3A can be in the form of a desktop computer or in the form of a laptop or tablet computer and may be a transportable data processing device having the form of at least one of: a handheld device; a user wearable device; and being part of a user transport vehicle (e.g., an in-dashboard data processing device).
Also in the shown first environment 300A, the user 301A is at times having a local data processing device 299 automatically sensing second signals 298 indicative of input types energetic attention giving activities ei(t, x, f, {TS, XS, . . . }) of the user (another form of attention giving energies), where here, ei denotes input type energetic attention giving activities of the user 301A which activities ei have at least a time t parameter associated therewith and optionally have other parameters associated therewith such as but not limited to, x: physical location at which or to which attention is being given (and optionally v: for velocity and a: for acceleration); f: distribution in frequency domain of the attention giving activities; Ts: associated nodes or regions in topic space that more likely correlate with the attention giving activities; Xs: associated nodes or regions in a system maintained context space that more likely correlate with the attention giving activities (where context can include a perceived physical or virtual presence of on-looking other users if such presence is perceived by the first user); Cs: associated points or regions in an available-to-user content space; EmoS: associated points or regions in an available-to-user emotions and/or behavioral states space; Ss: associated points or regions in an available-to-user social dynamics space; and so on. (See also and briefly again the lower half of FIG. 3D).
Also represented for the first environment 300A and the user 301A is symbol 301 xp representing the surrounding physical contexts of the user and signals (also denoted as 301 xp) indicative of what some of those surrounding physical contexts are (e.g., time on the local clock, location, velocity, etc.). Included within the concept of the user 301A having a current (and perhaps predictable next) surrounding physical context 301 xp is the concept of the user being knowingly engaged (known or believed by the user 301A) with other social entities where those other social entities (not explicitly shown) are knowingly/believed to be there because the first user 301A knows or believes they are attentively there, and such knowledge/belief can affect how the first user behaves, what his/her current moods, social dynamic states, etc. are. The attentively present, other social entities may connect with the first user 301A by way of a near-field communications network 301 c such as one that uses short range wireless communication means to interconnect persons who are physically close by to each other (e.g., within a mile) or they may be physically in the presence of the first user 301A or engaged with him/her by means of televideo conferencing or the like.
Referring in yet more detail to possible elements of the output type first signals 302 that are indicative of energetic output expressions Eo(t, x, f, {TS, XS, . . . }) of the user, these may include user identification signals actively produced by the user (e.g., password) or passively obtained from the user (e.g., biometric identification). These may include energetic clicking, tapping and/or typing and/or copying-and-pasting and/or other touching/gesturing signal streams produced by the user 301A in corresponding time periods (t) and within corresponding physical space (x) domains where the latter click/tap/etc. streams or the like are input into at least one local data receiving and/or processing device 299 (there could be more), and where the device(s) 299 has/have appropriate graphical and/or other user interfaces (G+UI) for receiving the user's energetic, and attention giving-indicative streams 302. The first signals 302 which are indicative of energetic output expressions Eo(t, x, f, {TS, XS, . . . }) of the user may yet further include facial configurations (e.g., intentional eyebrow raises, lip pursings, puckerings, tongue projections and/or movements) and/or head gestures and/or other body gesture streams produced by the user and detected and converted into corresponding data signals. They may include voice and/or other sound streams produced by the user, biometric streams produced by or obtained from the user, GPS and/or other location or physical context steams obtained that are indicative of the physical context-giving surrounds (301 xp) of the user, data streams that include imagery or other representations of nearby objects and/or persons where the data streams can be processed by object/person recognizing automated modules and thus augmented with informational data about the recognized object/person (see FIG. 2), and so on. In one embodiment, the determination of current facial configurations may include automatically classifying current facial configurations under a so-called, Facial Action Coding System (FACS) such as that developed by Paul Ekman and Wallace V. Friesen (Facial Action Coding System: A Technique for the Measurement of Facial Movement, Consulting Psychologists Press, Palo Alto, 1978; incorporated herein by reference). In one variation these codings are automatically augmented according to user culture or culture of proximate other persons, user age, user gender, user socio-economic and/or residence attributes and so on.
Referring to possible elements of the input type second signals 298 that are indicative of energetic but not outputting, attention giving activities ei (t, x, f, {TS, XS, . . . }) of the user, these can include eye tracking signals that are automatically obtained by one of the local data processing devices (299) near the user 301A, where the eye tracking signals (e.g., as tracked over time and statistically processed to identify the predominant points, lines or curves of focus) may indicate how attentive the user is and/or they may identify one or more objects, images or other visualizations that the user is currently giving predominant energetic attention to by virtue of his/her eye activities (which activities can include eyelid blinks, pupil dilations, changes in rates of same, etc. as alternatives to or as additions to eye focusing and eye darting actions of the user). The energetic attention giving activities ei (t, x, f, {TS, XS, . . . }) of the user may alternatively or additionally include not fully intentional head tilts, nods, wobbles, shakes, etc. where some may indicate the user is listening to or for certain sounds, nostril flares that may indicate the user is smelling or trying to detect certain odors, eyebrow raises and/or other facial muscle tensionings or relaxations that may indicate the user is particularly amused or otherwise emotionally moved by something he/she perceives, and so on but is not intentionally trying to communicate something to someone or to his/her machine by means of such not fully intentional body language factors. Categorization of body language factors into being intended versus not fully intentional may be based on the currently activated PEEP record (Personal Emotions Expression Profile) of the user where the PEEP record includes a lookup table (LUT) and/or knowledge base rules (KBR's) differentiating between the two kinds of body language factors.
In the illustrated first environment 300A, at least one of the user's local data processing devices (299) is operatively coupled to or includes as a part thereof of web content displaying and/or otherwise presenting means (e.g., a flat panel display and/or sound reproducing components). The at least one of the user's local data processing devices (299) is further operatively coupled to and/or has executing within it, a corresponding one or more network browsing modules 303 where at least one of the browsing modules 303 is causing a presenting (e.g., displaying) of browser generated content to the user, where the browser-provided content 299 xt can have one or more of positioning (x), timing (t) and spatial and/or temporal frequency (f) attributes associated therewith. As those skilled in the art may appreciate, the browser generated content may include, but is not limited to, HTML, XML or otherwise pre-coded content that is converted by the browsing module(s) 303 into user perception-friendly content. The browser generated content may alternatively or additionally include video flash streams or the like. In one embodiment, the network browsing modules 303 are cognizant of where on a corresponding display screen or through another medium various sub-portions of their content is being presented, when it is being presented, and thus when the user is detected by machine means to be then casting input and/or output energies of the attentive kind to the sources (e.g., display screen area) of the browser generated sub-portions of content (299 xt, see also for example sub-portions 117 a of window 117 of FIG. 1A), then the content placing (e.g., positioning) and timing and/or other attributes of the browsing module(s) 303 can be automatically logically linked to the detected focusing of user input and/or output energies (Eo(x, t, . . . ), ei(x, t, . . . ) based on time, space and/or other metrics and the logical links for such are relayed to an upstream net or web server 305 or directly to a further upstream portion 310 of the STAN—3 system 410. (As used herein, a “web server” is understood to be a physical or virtual computer that is configured, in accordance with industry-provided standards, to respond to industry-recognized serving requests from web browsers and to responsively serve up web content for downloading to the browser where the downloaded content is coded according to industry-recognized standards so that such content can be subsequently decoded by a target browser module (e.g., 303) that is configured in accordance with the same or similar industry-recognized standards and so that such content can then be presented in decoded form to the user.) In one embodiment, the one or more browsing module(s) 303 are modified (e.g., instrumented) beyond minimal industry-recognized standards for web browsing and by means of a software plug-in or the like to internally generate signals representing the logical linkings between the various sub-portions of browser produced content, its timing and/or its placement and the attention indicating other focus indicating signals (e.g., 298, 302) produced by the local focus detecting instrumentalities (e.g., eye-tracking mechanisms). In an alternate embodiment, a snooping module is added into the data processing device 299 to snoop out the content placing (e.g., positioning) or other attributes of the browser-produced content 299 xt and to link the attention indicating other signals (e.g., 298, 302) to those associated placement/timing attributes (x,t) and to relay the same upstream to unit 305 or directly to unit 310. In another embodiment, the web/net server 305 is modified to automatically generate data signals that represent the logical linkings between browser-generated sub-portions of content (299 xt) and one or more of the attention energies indicating signals and/or context indicating signals: Eo(x, t, . . . ), ei(x, t, . . . ), Cx(x, t, . . . ), etc. produced by the local focus detecting instrumentalities and by local context determining instrumentalities (e.g., GPS unit).
When the STAN—3 system portion 310 receives the combination (322) of the content-sub-portion identifying signals (e.g., time, place and/or data of browser-generated content 299 xt) and the signals representing user-expended attention-giving energies (Eo(x, t, . . . ), ei(x, t, . . . )) cast on those sub-portions and/or user-aware-of context indicators Cx(x, t, . . . ), etc., the STAN—3 system portion 310 can treat the same in a manner generally similar to how it treats directly uploaded CFi's (current focus indicator records) of the user 301A. The STAN—3 system portion 310 can therefore produce responsive result signals 324 for use by the web/net server 305 or a further downstream unit, where the responsive result signals 324 may include, but not limited to, identifications of the most likely topic nodes or topic space regions (TSR's) within the system topic space (413?; or another such space if applicable) that correspond with the received combination 322 of content, focus and/or context representing signals. In one embodiment, the number of returned as likely, topic node (or other node) identifications is limited to a predetermined number such as N=1, 2, 3, . . . and therefore the returned topic/other node or subregion identifications may be referred to as the top N topic node/region ID's in FIG. 3A.
Although topic space is mentioned as a convenient example, it is fully within the contemplation of the present disclosure for the responsive result signals 324 (produced by the STAN—3 system 310) to represent points, nodes or subregions of other system-maintained Cognitive Attention Receiving Spaces such as, but not limited to, keyword space, URL space, social dynamics space and so on. The responsive result signals 324 may be seen as results of having tapped into the collection of collective Cognitive Attention Receiving Spaces maintained by the system 310 and having selectively extracted from that “collective brain” (in a manner of speaking) the informational resources maintained by that “collective brain”, including, but not limited to, most currently popular chat or other forum participation sessions directed to the corresponding points, nodes or subregions of system-maintained Cognitive Attention Receiving Spaces (e.g., topic space) where the corresponding points, nodes or subregions may be selected on a context-sensitive basis. Context-based selection is possible because the context representing signals Cx(x, t, . . . ) of the first user 301A are input into the STAN—3 system 310 and because (as shall be better detailed below), the STAN—3 system 310 maintains hybrid spaces whose nodes can point to context-specific nodes of other spaces and/or chat or other forum participation opportunities or other informational resources that cross-correlate with the hybrid space nodes. Just as the purebred or non-hybrid Cognitions-representing Spaces (e.g., topic space, keyword space, URL space, etc.) have consensus-wise created PNOS-type points, or nodes or subregions respectively representing consensus-wise defined, communal cognitions associated with the purebred types of cognitions, the hybrid Cognitions-representing Spaces (e.g., topic-plus-context space) have stored therein, consensus-wise created PNOS-type points, or nodes or subregions respectively representing consensus-wise defined, communal cognitions associated with the hybrid types of cognitions. For example, when the topic of “football” is taken within the context of being at Ken's house (see again the introductory hypothetical) and it being SuperBowl Sunday™ that day and the first user's calendaring database indicating that he has clean-up crew duty that hour, the system can identify a corresponding and context-based PNOS-type point, node or subregion in a corresponding topic-plus-context space subregion that points to co-associated chat or other forum participation opportunities that other users in similar contextual situations would likely want to participate in. Yet more specifically, one such online chat room might be directed to the topic of “How to finish your clean-up assignments without missing high points of today's game”. In other words, rather than the user having to fish through many possible chat rooms looking for one specifically directed to his unique situation, other users whose current attention giving energies are focused-upon the same or a substantially similar node in the same subregion of topic-plus-context space are brought together and invited to simultaneously or in close temporal proximity, join in on a chat or other forum participation session linked to that combination of context plus topic.
As explained in the here-incorporated STAN—1 and STAN—2 applications, each topic node within the system-maintained topic space may include pointers or other links to corresponding on-topic chat rooms and/or other such forum participation opportunities. The linked-to forums may be sorted, for example according to which ones are most popular among different demographic segments (e.g., age groups) of the node-using population. In one embodiment, the number returned as likely, most popular chat rooms (or other so associated forums) is limited to a predetermined number such as M=1, 2, 3, . . . and therefore the returned forum identifying signals may be referred to as the top M online forums in FIG. 3A. The nodes of a hybrid Cognitions-representing Space can operate in substantially the same except that the points, nodes or subregions of the hybrid space are dedicated to a corresponding hybridization of consensus-wise defined, communal cognitions.
As also explained in the here-incorporated STAN—1 and STAN—2 applications, each topic node may include pointers or other links to corresponding on-topic topic content that could be suggested as further research areas (non-forum types of informational resources) to STAN users who are currently focused-upon the topic of the corresponding node. The linked-to suggestible content sources may be sorted, for example according to which ones are most popular among different demographic segments (e.g., age groups) of the node-using population. In one embodiment, the number returned as likely, most popular research sources (or other so associated suppliers of on-topic material) is limited to a predetermined number such as P=1, 2, 3, . . . and therefore the returned resource identifying signals may be referred to as the top P on-topic other contents in FIG. 3A. The nodes of a hybrid Cognitions-representing Space can operate in substantially the same except that the points, nodes or subregions of the hybrid space will point to further resources dedicated to the corresponding hybridization of the consensus-wise defined, communal cognitions as represented by the respective points, nodes or subregions of the respective hybrid space.
As yet further explained in the here-incorporated STAN—1 and STAN—2 applications, each topic node may include pointers or other links to corresponding people (e.g., Tipping Point Persons or other social entities) who are uniquely associated with the corresponding topic node for any of a variety of reasons including, but not limited to, the fact that they are deemed by the system 410 to be experts on that topic, they are deemed by the system to be able to act as human links (connectors) to other people or resources that can be very helpful with regard to the corresponding topic of the topic node; they are deemed by the system to be trustworthy with regard to what they say about the corresponding topic, they are deemed by the system to be very influential with regard to what they say about the corresponding topic, and so on. In one embodiment, the number returned as likely to be best human resources with regard to topic of the topic node (or topic space region: TSR) is limited to a predetermined number such as Q=1, 2, 3, . . . and therefore the returned resource identifying signals may be referred to as the top Q on-topic people in FIG. 3A. The nodes of a hybrid Cognitions-representing Space can operate in substantially the same except that the points, nodes or subregions of the hybrid space will point to people who can serve as resources for the corresponding hybridization of the consensus-wise defined, communal cognitions as represented by the respective points, nodes or subregions of the respective hybrid space.
The list of topic-node-to-associated informational items can go on and on. Further examples may include, most relevant on-topic tweet streams, most relevant on-topic blogs or micro-blogs, most relevant on-topic URLs, most relevant on-topic online or real life (ReL) conferences, most relevant on-topic social groups (of online and/or real life gathering kinds), and so on. And also, of course, it is within the contemplation of the present disclosure for the produced responsive result signals 324 of the STAN—3 system portion 310 to be representative of informational resources extracted from, or by way of other Cognitive Attention Receiving Spaces maintained by the system besides or in addition to topic space.
The produced responsive result signals 324 of the STAN—3 system portion 310 can then be processed by the web or net server 305 and converted into appropriate, downloadable content signals 314 (e.g., HTML, XML, flash or otherwise encoded signals) that are then supplied to the one or more browsing module(s) 303 then being used by the user 301A where the browsing module(s) 303 thereafter provide the same as presented content (299 xt, e.g., through the user's computer or TV screen, audio unit and/or other media presentation device).
More specifically, the initially present content (299 xt) on the user's local data processing device 299, before that initial content (299 xt) is enhanced (supplemented, augmented) by use of the STAN—3 system 310; may have been a news compilation web page that was originated from the net/web server 305, converted into appropriate, downloadable content signals 314 by the browser module(s) 303 and thus initially presented to the user 301A. Then the context-indicating and/or focus-indicating signals 301 xp, 302, 298 obtained or generated by the local data processing devices (e.g., 299) then surrounding the user are automatically relayed upstream to the STAN—3 system portion 310. In response to these, unit 310 automatically returns response signals 324. The latter flow downstream and in the process they are converted into on-topic, new (post-initial) displayable information (or otherwise presentable information; e.g., audible information) that the user may first need to approve/accept before a final presentation is provided (e.g., after the user accepts a corresponding invitation to enter an online chat room) or that the user is automatically treated to without need for invitation acceptance. This new, post-initial and displayable and/or otherwise presentable information (e.g., encoded by downstream heading signals 314) can enhance the initial web-using experience of the respective user 310A by for example automatically including or suggesting for inclusion, currently hot and on topic chat or other forum participation opportunities that are or will be populated by co-compatible other users.
Yet more specifically, in the case of the initial news compilation web page (e.g., displayed in area 299 xt at first time t1), once the system automatically determines what topics and/or specific sub-portions of the initially available content the user 301A is currently more focused-upon (e.g., energetically paying attention more to and/or more energetically responding to), the initially presented news compilation transforms automatically and shortly thereafter (e.g., within a minute or less) into a “living” news compilation that seems to magically know what the user 301A has currently been focusing-upon (casting significant attention giving energies upon) and which then serves up correlated additional content (e.g., invitations to immediately join in on related chat rooms and/or suggestions of additional resources the user might want to investigate) which the user 301A likely will welcome as being beneficially useful to the user rather than as being unwelcomed and annoying. Yet more specifically, if the user 301A was reading a short news clip about a well known entertainment celebrity (movie star) or politician named X, or sports figure (e.g., Joe-the-Throw Nebraska (fictitious)), the system 299-310 may shortly thereafter automatically pop open a live chat room (or invitation thereto) where like-minded other STAN users are starting to discuss a particular aspect regarding celebrity X that happens to now be predominantly on the first user's (301A) mind. The way that the system 299-310 came to infer what was most likely receiving the more significant attention giving energies within the first user's (301A) mind is by utilizing a trial and error technique in combination with the system-maintained Cognitive Attention Receiving Spaces (CARSs) where the trial and error technique makes a first guess at likely points, nodes or subregions in the CARSs that the user might agree he/she is focusing his/her attention giving energies upon, then presenting corresponding content (e.g., invitations) to the user, then collecting implicit or explicit vote indicators (CVi's) respecting the newly presented content and repeating so as to thereby home in on the most likely topics on the user's mind as well as homing in on the most likely context that the user is apparently operating under with aid of pre-developed profiles (301 p in FIG. 3D) for the logged-in first user (301A) and with aid of the then detected context-indicating and/or focus-indicating signals 301 xp, 302, 298 of the first user (301A).
Referring to the flow chart of FIG. 3C, a machine-implemented process 300C that may be used with the machine system 299-310 of FIG. 3A may begin at step 350. In next step 351, the system automatically obtains focus-indicating signals 302 that indicate certain outwardly expressed activities (attention giving activities) of the user such as, but not limited to, entering one or more keywords into a search engine input space, clicking, tapping, gesturing or otherwise activating and thus navigating through a sequence of URL's or other such pointers to associated content, participating in one or more online chat or other online forum participation sessions that link directly or indirectly (and strongly or weakly—see for example the session tethers of FIG. 3E) to predetermined topic nodes of the system topic space (413?), accepting machine-generated invitations (see 102J of FIG. 1A) that are directed to respective predetermined topic nodes, clicking, tapping on or otherwise activating expansion tools (e.g., starburst+) of on-screen objects (e.g., 101 ra?, 101 s? of FIG. 1B) that are pre-linked to predetermined topic nodes, focusing-upon community boards (see FIG. 1G) that are pre-linked to predetermined topic nodes, clicking, tapping on or otherwise activating on-screen objects (e.g., 190 a.3 of FIG. 1J) that are cross associated with a geographic location and one or more predetermined topic nodes, using the Layer-vator (113 of FIG. 1A) to ride to a specific virtual floor (see FIG. 1N) that is pre-linked to a small number (e.g., 1, 2, 3, . . . ) of predetermined topic nodes, and so on. Once again, mention here of predetermined topic nodes and informational resources that are logically linked thereto is to be appreciated as being representative of the broader concept of specifically identified PNOS-type points, nodes or subregions represented as such in one or more system-maintained Cognitive Attention Receiving Spaces (CARSs) and the informational resources (e.g., pointers to chat rooms and/or pointers to non-forum content) that are logically linked therewith.
In next step 352, the system automatically obtains or generates focus-indicating signals 298 that indicate certain inwardly directed (inputting types of) attention giving activities of the user such as, but not limited to, staring (e.g., having eye dart pattern predominantly hovering there) for a time duration in excess of a predetermined threshold amount at a specific on-screen area (e.g., 117 a of FIG. 1A) or a machine-recognized off-screen area (e.g., 198 of FIG. 2) that is pre-associated with a limited number (e.g., 1, 2, . . . 5) of topic nodes of the system 310; repeatedly returning to look at (or listen to) a given machine presentation of content where that frequently returned to presentation is pre-linked with a limited number (e.g., 1, 2, . . . 5) of such topic nodes and the frequency of repeated attention giving activities and/or durations of each satisfy predetermined criteria that are indicative for that user and his/her current context of extreme interest in the topics of such topic nodes, and so on.
In next step 353, the system automatically obtains or generates context-indicating signals 301 xp. Here, such context-indicating signals 301 xp may indicate one or more most likely contextual attributes of the user such as, but not limited to: his/her geographic location, his/her economic activities disposition (e.g., working, on vacation, has large cash amount in checking account, has been recently spending more than usual and thus is in shopping spree mode, etc.), his/her biometric disposition (e.g., sleepy, drowsy, alert, jittery, calm and sedate, etc.), his/her disposition relative to known habits and routines (see briefly FIG. 5A), his/her disposition relative to usual social dynamic patterns (see briefly FIG. 5B), his/her awareness of other social entities giving him/her their attention, and so on. See also FIG. 3J (context primitive data object) as described below.
In next step 354 (optional) of FIG. 3C, the system automatically generates logical linking signals that link the time, place and/or frequency of focused-upon content items with the time, place, direction and/or frequency of the context-indicating and/or focus-indicating signals 301 xp, 302, 298 so as to thereby create hybrid pointing signals (HyCFi's) that represent and/or point to the combination or clustered complex of current focus indicators (a CFi's cluster) and that indicate the context(s) under which such clusters were generated as well as, optionally, representing emotional intensity cross-correlated with the in-context cluster of signals representing corresponding user focusing activities. As a result of this optional step 354, upstream unit 310 receives a clearer indication of what specific sub-portions of content go with which focusing-upon activities and to what degree of user intensity (e.g., emotional intensity). As was mentioned above and will be seen in yet more detail below, in one embodiment, the STAN—3 system maintains so-called hybrid Cognitive Attention Receiving Spaces (see for example, hybrid node 384.1 of FIG. 3E) and one or more of such CARSs are hybrids of context plus something else (e.g., keywords, URL's, etc.). The generated hybrid signals (HyCFi's) of step 354 may be used to point to specific points, nodes or subregions in such hybrid CARSs where the latter nodes, etc. point to corresponding, context-appropriate further informational resources (e.g., live chat rooms and/or other resources).
In one embodiment the CFi's (or HyCFi's) received by the upstream unit 310 are time and/or place stamped. As a result of presence of such chronological and spatial identifications, the system 299-310 (FIG. 3A) may determine to one degree of resolution or another, which CFi's and/or HyCFi's likely belong or not with one another based on clusterings of the (Hy)CFi's around associated locations and/or timings and/or commonality of focused-upon sub-portions of content 299 xt. The (Hy)CFi's that are uploaded into the STAN—3 system 310 are therefore not necessarily treated as individualized samplings of attention giving activities of a corresponding user, but rather they can be treated as a more informative collection (integration) of interrelated hints and clues about what the user is focusing his/her attention giving energies upon. It is to be understood that it is merely helpful but not necessary that optional step 354 be performed.
In next carried out step 355 of FIG. 3C, the system automatically relays to the upstream portion 310 of the STAN—3 system 410 available ones of the context-indicating and/or focus-indicating signals 301 xp, 302, 298 as well as the optional context-to-focus linking signals (HyCFi's generated in optional step 354). The relaying step 355 may involve sequential receipt and re-transmission through respective units 303 and 305. However, in some cases one or both of units 303 and 305 may be bypassed. More specifically, data processing device 299 may relay some of its informational signals (e.g., CFi's, CVi's, HyCFi's) directly to the upstream portion 310 of the STAN—3 system 410.
In a next carried out step 356 of FIG. 3C, the cloud or otherwise-based STAN—3 system 410 (which includes unit 310) processes the received signals 322, produces corresponding result signals 324 and transmits some or all of them either to the net/web server 305 or it bypasses the net/web server 305 in the case of some of the result signals 324 are in appropriate format and instead transmits some or all of the result signals 324 directly to the browser module(s) 303 or directly to the user's local data processing device 299. The returned result signals 324 are then optionally used by one or more of downstream units 305, 303 and 299 for presenting the user with updated/upgraded/augmented content that may enhance the user's experience beyond that provided by the initially presented web content. More specifically, where a news stories compilation page (displayed web page—e.g., see 117 of FIG. 1A) may have initially presented the user with a wide variety of news articles; some garnering more attention from the user than others, the updated/upgraded/augmented version of that displayed web page (which is enhanced or updated by newer content provided on the basis of the result signals 324 generated by the STAN—3 system server(s) 310) will often appear to be more on target with respect to what the user is more interested on focusing-upon now. In other words, it will be more on-topic with respect to the top N now topics the user apparently has in mind at the present moment. As a result, a user-serving “living” news page is perceived by the user where that “living” news page appears to somehow have read the user's mind and then automatically zoomed in on the news stories and articles the user is now most interested in. So the “living” news page becomes a user-centric “living” news page that appears to serve the selfish private and current wants of the specific user rather than being merely a generalized news page that seeks to simultaneously please as many people as possible without actually zooming in on the selfish private and current wants of specific users and thus not truly pleasing any of them.
In next carried out step 357 of FIG. 3C, if the informational presentations (e.g., displayed content, audio presented content, etc.) changes as a result of machine-implemented steps 351-356, and the user 301A becomes aware of the changes and reacts to them (in a positive or negative voting way), then new context-indicating and/or focus-indicating signals and/or voting signals 301 xp, 302, 298, CVi's may be produced as a result of the user's positive, negative or neutral reaction to the new stimulus. Alternatively or additionally, the user's context and/or input/output activities may change due to passage of time or other factors (e.g., the user 301A is in a vehicle that is traveling through different contextual surroundings). Accordingly, in either case, whether the user reacts (Yes) or not (No), a subsequent process flow path 359 x loops back to step 351 so that content-refreshing step 356 may be repeatedly executed and thereafter followed again by step 351. Therefore the system 410 automatically keeps updating its assessments of where the user's current attention is in terms of topic space (see Ts of next to be discussed FIG. 3D), in terms of context space (see Xs of FIG. 3D), in terms of content space (see Cs of FIG. 3D) and/or in terms of likely to be focused-upon other PNOS-type points, nodes or subregions of other Cognitive Attention Receiving Spaces. At minimum, the system 410 automatically keeps updating its assessments of where the user's current attention is in terms of energetic expression outputting activities of the user (see output 3020 of FIG. 3D) and/or in terms of energetic attention giving activities of the user (see output 2980 of FIG. 3D).
If and when the user reacts emotionally in step 357 to the updated/upgraded content presented to the user by step 356, steps 358 a and 358 b may be executed. In step 358 a, the system automatically obtains reaction indicating signals (CVi's) from sensors surrounding the user (or even embedded on or in the user—e.g., intra-oral cavity instrumentation, intra-nasal cavity instrumentation, etc.) and the system determines whether or not to treat such emotion-indicating signals as implicit or explicit votes of confidence or no confidence regarding the newly updated/upgraded content based on the user's currently activated PEEP record. If for example, the user quickly re-focuses his/her attention upon the newly updated/upgraded content and reacts positively (e.g., smiles), then the STAN—3 system can treat this positive reaction as a reinforcement in step 358 b for neural networking-wise learning or like learned models (e.g., KBR's) the system has/is developed/developing for the user, for his/her current context, and for determining what the user apparently wants to then have presented (e.g., displayed) to him/her. On the other hand, if the user ignores the newly updated/upgraded content (generated by step 356) or reacts in a manner which indicates disapproval of how the STAN—3 system behaved (as opposed to disapproval directed to the newly updated/upgraded content itself), the system automatically alters its behavior (the system adaptively “learns”) in step 358 b so that hopefully the system will do better in the next go-around through steps 351-356. In other words, the learning loop that includes steps 358 a, 358 b and repetition pathway 359 x operates on a trial and error basis that is designed to urge the STAN—3 system into better servicing the user by taking note of his/her positive or negative reactions (if any, and in step 357) to service provided thus far and/or by also taking note of changing circumstances (changed context determined in step 353). As should be apparent from FIG. 3C, if there is no detected user reaction in step 357, the “No” path 359 n is taken into loop back path 359 x. On the other hand, if a significant user reaction is detected in step 357, the “Yes” path is taken into steps 358 a/358 b and thereafter path 359 y is followed into loop back path 359 x. In one embodiment, the reinforced or detracted from model of the first user includes at least one of the currently activated personhood profiles (CpCCp), domain specific profiles (DsCCP), personal emotion expression profiles (PEEP), habits and routines profiles (PHAFUEL) of the first user.
Before moving on to the details of FIG. 3D, a brief explanation of FIG. 3B is provided. The main difference between 3A and 3B is that units 303 (browser modules) and 305 (web servers) of 3A are respectively replaced by application-executing module(s) 303? (a.k.a. client modules 303?) and application-serving module(s) 305? in FIG. 3B. As those skilled in the art may appreciate, FIG. 3B is a more generalized version of FIG. 3A because a web browser is a special purpose species of a computer application program and a web server is a special species of a general application server computer (305?) that supports other kinds of computer application programs. Because the downstream heading inputs to application-executing module(s) 303? are not limited to browser recognizable codes (e.g., HTML, XML, flash video streams, etc.) and instead may include application-specific other codes, communications line 314? of FIG. 3B is shown to optionally transmit such application-specific other codes. In one embodiment, of FIG. 3B, the application-executing module(s)/clients 303? and/or application-serving module(s)/hosts 305? implement a user configurable news aggregating function and/or other information aggregating functions wherein the application-serving module(s) 305? for example automatically crawl through or search within various databases (e.g., accessed via network 401?) beyond the reach of the publically accessible parts of the internet as well as within the internet for the purpose of compiling for the user 301B, news and/or other information of a type defined by the user through his her interfacing actions with an aggregating function of the application-executing module(s) 303?. In one embodiment, the databases searched within or crawled through by the news aggregating functions and/or other information aggregating functions of the application-serving module(s) 305? include areas of the STAN—3 database subsystem 319?, where these database areas (319?) are ones that system operators of the STAN—3 system 410 have designated as being open to such searching through, or crawling through (e.g., without compromising reasonable privacy expectations of STAN users). In other words, and with reference to the user-to-user associations (U2U) space 311? of the FIG. 3B as well as the user-to-topic associations (U2T) space 312?, the topic-to-topic associations (T2T) space 313?, the topic-to-content associations (T2C) space 314? and the context-to-other (e.g., user, topic, etc.) associations (X2UTC) space 316?; inquiries 322? input into unit 310? may be responded to with result signals 324? that reveal to the application-serving module(s) 305? various data structures of the STAN—3 system 410 such as, but not limited to, parts of the topic node-to-topic node hierarchy then maintained by the topic-to-topic associations (T2T) mapping mechanism 413? (see FIG. 4D).
Referring now to FIG. 3D and the exemplary STAN user 301A? shown in the upper left corner thereof, it should now be becoming clearer that almost every word 301 w (e.g., “Please”), phrase (e.g., “How about . . . ?”), facial configuration (e.g., smile, frown, wink, tongue projection, etc.), head gesture 301 g (e.g., nod) or other energetic expression output Eo(x, t, f, . . . ) produced by the user 301A? is not to be seen as just that expression being output Eo(x, t, f, . . . ) in isolation but rather as one that is produced with its author 301A? being situated in a corresponding internal contextual state therefor and with the surrounding (external) context 301 x of its author 301A? also potentially being a context therefor and with each preceding or following expressive output Eo(x?, t+1, f?, . . . ) possibly providing additional contextual flavor to what comes after or before. (The proposition about external context 301 x being a factor depends on whether the user is blissfully unaware of his/her physical surroundings or more attuned to them.) Stated more simply, the user is the context of his/her actions and his/her contextual surroundings can also be part of the context and his/her surrounding other expressions can further be part of the context. The operative context for each user output expression Eo(x, t, f, . . . ) can give clearer meaning (in a semantic or other sense) to the machine detected, attention giving activities of the user. Therefore, and in accordance with one aspect of the present disclosure, the STAN—3 system 410 maintains as one of its many data-objects organizing spaces (which Cognitive Attention Receiving Spaces or CARSs are defined by stored representative signals stored in machine memory), a context nodes organizing space 316?. In FIG. 3D, this context nodes organizing space 316? is illustrated as an inverted square pyramid within which there are sub-portions defined as context subregions (e.g., XSR1, XSR2). In one embodiment, the context nodes organizing space 316?, or context space 316? for short, includes context defining primitive nodes (see FIG. 3J) and combination operator nodes (see for example 374.1 of FIG. 3E) including those that define a hybrid combination of a context parameter and a parameter from a non-context other CARS (e.g., keyword space, URL space, etc.). As used herein, a “primitive” is a data structure representing one or more fundamental “symbols” or “codings” where the latter represent a comparatively simple cognitive concept and whereby more complex cognitive concepts can be represented by operator nodes that reference the primitives to build with and from them to arrive at more complex cognitive concepts. For example, one possible and simple concept within context space might be: “This social entity is now operating within his/her normal work hours” and the corresponding coding might be: “Context(t1,p1) includes Time=WithinNormalWorkHours” where t1 is a time range indicating when the context is valid and p1 is a probability factor whose value may indicate that this version of Context is the most probable one (but not necessarily the only likely one). Another primitive construct within context space might represent the concept of: “Today is Wednesday” and the corresponding coding might be: “Context(t1,p1) includes Day=Wednesday”. A combination forming, operator may combine the two more primitive codings (primitive representing symbols) to form the more complex concept of: “Today is Wednesday AND this social entity is now operating within his/her normal work hours”. The node having that operator in it will then represent that more complex contextual state. Of course, the preceding is merely a simple example and much more complex representations of complex contextual states may be devised with use of primitives and operator nodes that reference to them, as shall be detailed later below. See for example, node 374.1 of FIG. 3E. The term “primitive” as used herein is not to be construed as meaning that the present disclosure does not admit for yet more primitive codings than, for example the exemplary primitive data structure of, say, FIG. 3W (textual cognition representing primitive data structure). Although the concept of a cognition representing primitive is a somewhat simple one, the data structures used to support a communally created and communally updateable one can be more complex as shall become evident below. The definition of “primitive” as used herein does not require communal createability and communal updateability even though such are desirable functionalities herein.
Accordingly, a user's current context can be viewed as an amalgamation of concurrent context primitives and/or temporal sequences of such primitives (e.g., if the user is multitasking and thus jumping back and forth between different contexts). More specifically, a user can be assuming multiple roles at one time where each role has a corresponding one or more activities or performances expected of it and the expressive outputs Eo(x, t, f, . . . ) produced by the user while in each respective contextual state are colored by the respective contextual state. The context primitives aspect of this disclosure will be explained in more detail in conjunction with FIG. 3J. The present FIG. 3D, which is now being described, provides more of a bird's eye view of the system and that bird's eye view will be described first. Various possible details for the data-objects organizing spaces (or “spaces” in short) will be described later below.
Because various semantic spins and/or other cognitive senses can be inferred from the “context” or “contextual state” of the user and can then be attributed for example to each output word 301 w of FIG. 3D (e.g., “Please”), to each facial configuration (e.g., raised eyebrows, flared nostrils) and/or head gesture (e.g., tilted head) 301 g, to each internal biometric state that is machine detected (e.g., tongue pressed against instrumented tooth cap), to each sequence of words (e.g., “How about . . . ?”) when such a sequence is assembled, to each sequence of mouse clicks, screen taps, gestures or other user-to-machine input activations, and so forth; proper resolution of current user context to one degree of specificity or another can be helpful to the STAN—3 system in determining what semantic spin and/or other cognitive sense(s) is/are more likely to be associated with one or more of the user's energetic input ei(x, t, f, . . . ) and/or output Eo(x, t, f, . . . ) activities. Proper resolution of current user context can also be helpful to the STAN—3 system in determining which CFi and/or CVi signals are to be grouped (e.g., clustered and/or cross-associated) with one another when parsing received CFi, CVi signal streamlets (e.g., 151 i 2 of FIG. 1F)). A simple example of semantic spin may be one where the user 301A? is giving attentive energies to the expression, “Lincoln”. (This example will be played on in yet more detail below.) The more likely semantic spin that is to be attributed by the STAN—3 system to the expression, “Lincoln” depends on what context(s) (signal 316 o) the system currently assigns to the respective user. The expression, “Lincoln” might refer to Abraham Lincoln, the 16th president of the United States. On the other hand, the same expression, “Lincoln” might refer to a U.S.A. car company founded in 1915 and later acquired by the Ford Motor Company. Yet alternatively, the same expression, “Lincoln” might refer to a city in the State of Nebraska (from which our fictitious football hero, Joe-the-“L”-Bow Throw hails and also from which his lesser known cousin, Tom the “T”-Bow Throw hails—also a fictitious football hero). If the STAN—3 system determines that the user context is that of being a Fifth Grade student doing his/her History homework, that will urge the system into putting a firstly directed, semantic spin on the exemplary expression, “Lincoln”. If, on the other hand, the STAN—3 system determines that the user context is that of being a working adult whose 10 year old car is currently giving him/her trouble and the person is thinking of buying a new car, that determined context will urge the system into putting a secondly directed, and different semantic spin on the exemplary expression, “Lincoln”. And yet further, if the STAN—3 system determines that the user context is that of being at Ken's house, ready to partake in a Superbowl™ Sunday Party (as described above), that determined context will urge the system into putting a thirdly directed, and yet again different semantic spin on the exemplary expression, “Lincoln”. The attributed semantic spin will cause the system to reference respective different clustering areas in primitive expression layers (see for example layer 371 of FIG. 3E) as will be explained later below.
Determination of the semantic/other-sense spin that is to be attributed to various individual and user focused-upon expressions (e.g., “Lincoln”) is not limited to the processing of individualized user actions per se (e.g., clicking tapping or otherwise activating user interface means such as hyperlinks, menus, etc.), it may also be used in the clustering together and processing of sequences of user actions. For example, if the user context is determined to be that of the Fifth Grade student doing his/her History homework and the user is detected to also concurrently focus-upon the expression, “war”, then the system can logically combine the two and determine the combination to be likely pointing to Abraham Lincoln's involvement with the U.S. Civil War. Once again, this aspect of automatically determining most likely combinations of individual expressions may rely on a pointing to different clustering areas in primitive expression layers (see for example layer 371 of FIG. 3E) as will be explained later below.
Stated more simply here, the machine determined ones of likely context(s) of the user (as represented by a signal 316 o output from the context determining mechanism 316? of FIG. 3D) are generally combined with the machine detected mouse clickings, screen tappings and/or other activities of the user 301A?, where a sequence of such actions may take the user (virtually) through a navigated sequence of content sources (e.g., web pages) and/or the latter may cause the STAN—3 system to model the user as virtually taking a journey (see also unit 489 of FIG. 4D) through a sequence of user virtual “touchings” upon nodes or upon subregions in various system-maintained spaces, including topic space (TS) for example. User actions taken within a corresponding “context” may also cause the STAN—3 system to model the user as being virtually transported through corresponding heat-casting kinds of “touching” journeys (see also 131 a, 132 a of FIG. 1E) past topic space nodes or topic space regions (TSR's), and so on. Thus; it is useful for the STAN—3 system to define; in a communal consensus-wise created sense, a context space (Xs) whose data-represented nodes and/or context space regions (XSR's) define in a communal consensus-wise agreed to sense, different kinds of, contextual states that the user may likely enter into in-his/her-mind. The so-identified contextual states of the user, even if they are identified in a “fuzzy” way rather than with more deterministic accuracy or fine resolution can then indicate which of a plurality of pre-specified user profile records 301 p should be deemed by the system 410 to be the currently active profiles of the user 301A?. The currently deemed to be active profiles 301 p may then be used to determine in an automated way, what topic nodes or topic space regions (TSR's) in a corresponding defined topic space (Ts) of the system 410 (or more generally which points, nodes or subregions of system-maintained CARSs) are most likely to represent the topics (or other kinds of cognitions) that the user 301A? is most likely to be currently focusing his/her cognition energies upon based on the in-context, machine-detected activities of the user 301A?. Of importance, the apparent “in-his/her-mind contextual states” mentioned here should be differentiated from physical, external contextual states (301 x) of the user. Examples of physical contextual states (301 x) of the user can include the user's physical identity (e.g., height, weight, fingerprints, body part dimensions, current body part orientations, etc.), the user's geographic location (e.g., longitude, latitude, altitude, direction faced by the user's face, etc.), the user's physical velocity relative to a predefined frame (where velocity includes speed and direction components), the user's physical acceleration vector and so on. Moreover, the user's physical contextual states (301 x) may include descriptions of the actual (not virtual) surroundings of the user, for example, indicating that he/she is now physically seated and forward facing in a vehicle having a determinable location, speed, direction and so forth. It is to be understood that although a user's physical contextual states (301 x) may be one set of states, the user can at the same time have a “perceived” and/or “virtual” set of contextual states that are different from the physical contextual states (301 x). More specifically, when watching a high quality 3D movie, the user may momentarily perceive that he or she is within the fictional environment of the movie scene although in reality, the user is sitting for example in a darkened movie theater. The “in-his/her-mind contextual states” of the user (e.g., 301A?) may include virtual presence in the fictional environment of the movie scene and the latter perception may be one of many possible “perceived” and/or “virtual” set of contextual states defined by the context space (Xs) 316? shown in FIG. 3D.
More generally, and just to summarize the above (and perhaps overly long winded) passages: the user is part of his/her own context. The user's current memories (e.g., recent history) and current state of awareness can be part of his/her context. The user's current physical identity and current physical surroundings and/or the user's current biological states and/or the user's current chronological positioning within time as well as spatial positioning can be part of his/her context and the user's current context. Sensor detectable ones of context-indicating states (which sensor signals are collectively denoted as XP in FIG. 3D and emanate from 301 x) can impart finer semantic spin and/or other resolution enhancing attributes to current focus indicator signals (CFi's) developed for the given user 301A?. In one embodiment, rather than transmitting raw focus indicator signals (CFi's) to the STAN—3 system, a machine-implemented method automatically transmits context-augmented or context-hybridized focus indicator signals (HyCFi's) to the STAN—3 system. The context-hybridized focus indicator signals (HyCFi's) may include one or more of context indicating informational signals such as, time of data collection, place of data collection, identification of the user (because the user is his/her own context); identification of other machines and/or social entities in the proximate neighborhood (real or virtual) of the data collecting machine, biometric telemetry collected by user proximate sensors, and so on. Context or context-hybridized focus indicator signals (HyCFi's) may be used to select a user's currently activated profile records (e.g., PEEP, CpCCp, PHAFUEL, etc.).