Profile-responsive system for information exchange in human- and device-adaptive query-response networks for task and crowd management, distributed collaboration and data integration

• US 8,639,650 B1
• Filed: 06/16/2010
• Issued: 01/28/2014
• Est. Priority Date: 06/25/2003
• Status: Active Grant

• Current Assignee: Susan Pierpoint Gill
• Original Assignee: Susan Pierpoint Gill
• Inventors: Gill, Susan Pierpoint
• Primary Examiner(s): Chaki, Kakali
• Assistant Examiner(s): COUGHLAN, PETER D
• Application Number:
  US12/817,167
• Time in Patent Office: 1,322 Days
• Field of Search: 706/61
• US Class Current: 706/61
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 3/04817 using icons graphical or visual programming using iconic symbols G06F8/34
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06Q 10/06311 Scheduling, planning or task assignment for a person or group
• CPC Class Codes: G06Q 10/101 Collaborative creation, e.g. joint development of products or services
• CPC Class Codes: G06Q 30/0611 Request for offers or quotes
• CPC Class Codes: H04L 65/403 Arrangements for multi-party communication, e.g. for conferences data switching systems for conference H04L12/18; arrangements for connecting several subscribers to a common circuit, i.e. affording conference facilities H04M3/56; television conferencing systems H04N7/15

Abstract

Provided is a computer-implemented system and method for task allocation and distributed collaboration in a sender-receiver, query-response network that augments internet-based social networks with decision support such that private, personally targeted, timely, geo-located, tagged information enables users to contribute and respond to requests using natural language, receive postings customized to their user needs and preferences, and contribute to the collection, interpretation, aggregation, integration and distribution of data, enabling rapid status updates, reporting, and performance management in requester-responder networks that entail information-sharing, task distribution, crowd management and collaborative human-machine problem-solving across a diversity of computer, mobile and device platforms.

Claims

1. A computer system for serving distributed client computers and mobile devices in a social network, wherein the computer system links distributed users, participating through multiple communication channels, with different levels of authorship and permissions,

said computer system comprising:

one or more network interface;

one or more processor for performing instructions for;

combining collective intelligence methods for processing data from anonymous users with collaborative intelligence methods wherein user contributions are credited and tagged to individual users to make searchable contributor fingerprints which comprise the total record of contributor actions in the system;

enlisting entries from, and querying, distributed users and agents;

receiving and parsing natural language user entries to tag, categorize, group, classify attributes, and integrate diverse entries;

generating new queries based upon task requester and user needs, as well as user performance capability, as defined by prior performance and assessments, tagged to user profiles;

maintaining individual responses private, anonymous, and independent of each other when responders should not be influenced by each others'"'"' responses;

making responses visible and credited, as specified by the task requester, by each participant, and/or by task design;

providing regular updates on the globally integrated response status, visible to the social network designated by the specific process, thus enabling user input as specified by task design;

publishing selected responses for comment, rating or vote from distributed user-responders when an iterative approach can achieve convergence;

one or more data storage device for storing said instructions.

2. The computer system of claim 1, wherein the system further comprises

data processing units, serving and connecting one or more communication channels;

data analyzers able to receive, rate, cluster according to filtering criteria, search, tag and perform operations on data generated by users and gathered by the system;

search algorithms, based on “

user fingerprints,”

task requester needs, and system requirements; and

clustering algorithms to group like users into subgroups, on which various automated procedures can be performed, wherein said procedures comprise, statistical analysis, predictive calculations, market and risk analysis, rating, tallying, grouping, tagging, sorting, linking user profiles, aggregating, integrating, targeting, publishing, or retaining as confidential.

3. The computer system of claim 1, wherein the instructions further comprise:

gathering information from, and about, users such that this information can be easily customized as demanded by the domain application and its task requirements;

broadcasting queries or task requests and gathering entries or responses such that diverse knowledge, assessments, and expertise of service providers in a social network can be engaged to make the event or task performance successful;

adjusting and customizing system behavior to support different levels of user expertise and different types of user participation;

enabling users to participate anonymously, or to be credited, or implementing a setting that determines which input is anonymous, and which credited.

4. The system of claim 1, wherein the instructions further comprise:

authenticating each user;

defining each user'"'"'s unique user fingerprints as a combination of user profile, preferences, and said user'"'"'s activity as tracked by the system;

enabling users to invite others to join the network, contribute or respond to entries, submit and respond to task requests, other queries, and other information;

enabling users to search the network, including, but not limited to, using keywords, profile and entry tags, and accessing responses to queries, not only by user name, but also by tagged content, geographical location, and time of response;

enabling users to respond to queries, task requests, or other input via an alpha-numeric or graphical user interface, whereby users can submit quantitative, text-based, verbal, or multiple choice responses to queries or other entries, including task requests and responses;

receiving user entries from mobile devices, computers or related apparatus, such that user data and other task related data is automatically classified into a processing network and retrievable through one or more channels as defined by the system.

5. The computer system of claim 1 wherein, after a registered user, who has set up a profile and preferences in the system, logs in, a dashboard is presented with a menu list of setup items corresponding to the buttons on the user interface, such that the user has options, which comprise:

picking conference talks and events to attend that will trigger the “

starting now”

alert button;

highlighting a map of the tradeshow floor with booths to attend;

selecting preferences, which determine how priority alerts are received; and

editing and augmenting preferences, and evolving each user'"'"'s fingerprints through use of the system.

6. The computer system of claim 1, wherein constraints can be customized, said constraints comprising one or more geo-locational, physical attribute, time or task constraint.

7. The system of claim 1 wherein new content can be added on-the fly by users in one or multiple channels, addressed to users in the same or other channels, such as from organizers to organizers, or from organizers to attendees, and including, but not limited to, content from organizers, sponsors, and users, said system allowing different categories of authorship, readership, permissions, content filtering, and access.

8. The system of claim 1 wherein entitlement permissions are adjustable as needed, and where categories of permissions, and means of granting permissions, can be revised, ranging from confidential to public, from anonymous to credited to the contributor, from published and readable, to open for comment, or with permission to edit.

9. The system of claim 1, employing a nine icon tic-tac-toe touch-screen for mobile devices, computer or other user interface, guiding the user through a step-by-step Query-Response or Task Requester-Responder sequence, which is followed in a natural clockwise sequence around the screen, or as needed by the user, where the ninth central button is used as the submit button, as a “

starting now”

or alerts button, or for other core functions.

10. The system of claim 1, wherein the system evolves as a result of both individual and aggregate behavior of users, and the overall status of the problem-solving process, wherein behaviors of the system respond to individual user participation, and to data on user behavior, response to incentives, capacity to engage other users, level of expertise and contribution to the system.

11. A computer-implemented method using natural language to elicit, receive, and organize information across diverse platforms comprised of servers, client computers and client mobile devices, using wireless, Wide Area Networks, and Local Area Networks, wherein non-structured natural language entries, queries and responses are converted to structured components that can be tagged, analyzed, searched, clustered, sorted and integrated Intelligent Integrating System to satisfy task requirements, user preferences, problem-solving constraints and trade-offs, and to deliver information as needed in response to user requests, profiles, preferences and past usage activity in the system, wherein coding of data enables data representation and data integration, further comprising:

classifying entries or query responses received, said classifying based on the type of entry or query intake;

time-stamps when contributions are submitted, and/or timestamp category clusters;

capacity to turn the time-stamp function on or off as determined by task needs;

geographic locators, wherein contributions are geographically located when submitted and/or clustered under geographic locator categories;

capacity to turn the geographic locator function on or off as determined by task needs;

context-coded and topic-coded natural language classifications and other tags;

relationship mapping, such that clusters augment user private-to-the-system profiles, which can be accessed from multiple nodes, and retrieved in various ways; and

updating private-to-the-system user profiles based upon preferences, system usage, entries and query responses received from each user.

12. The computer-implemented method of claim 11, wherein an embedded continual assessment tool produces data assessing user and task performance, recording how users participated, and their preferences.

13. The computer-implemented method of claim 11, wherein geographic locators, tagging user inputs and responses, allow geographic analysis of user needs and resources, and capabilities to meet those needs by the Intelligent Integrating System, specifying queries by neighborhood, city, region, or other geographically defined category, clustering responses by location and other relevance factors, producing profile analyses of users, and comparative clustering across geographic categories with similar challenges and attributes, enabling geographically specified sub-routines to be specified by task requesters to the query system running in a defined region.

14. A system for network-based collaborative problem-solving capable of guiding a plurality of users with divergent views toward a convergent problem resolution using an Intelligent Integrating System, wherein the location and identity of the Intelligent Integrating System (IIS) can be distributed, reside in the cloud, or change without any perceivable experience of system change by the users, said system comprising non-transitory computer readable storage media, including program logic embedded therein that causes control circuitry to perform the following steps:

accessing user input;

comparing multiple user inputs;

identifying gaps and querying for missing information if responses do not provide complete information;

generating a plan responsive to critical path task execution requirements and perceived knowledge gaps;

generating queries based upon user profiles, preferences, and prior user activity in the system;

storing data in a repository accessible on the network, responsive to a context that requires identifying, collecting, and utilizing a pool of background data to generate analyses and subsequent queries;

generating and publishing, either to all users, or to a cluster of selected users, status reports or new queries on-the-fly based on comparative analysis of user inputs, profile analysis, geographic location, or identifying missing data points, thereby recognizing that the users or the system need further information;

converting natural language, text-based responses, choice clicks, and data into formats for categorization at different levels of detail;

accessing and tagging entries from humans, computer agents and devices;

comparing and, where appropriate, summing the input;

rating and tagging query responses of each agent, based upon the distance of that agent'"'"'s input from the summation value;

defining each agent'"'"'s profile based upon the consensual or outlier status of each entry contributed by that agent;

summing profiles to examine the population of agents, subgroups, and users as a whole; and

examining consensus, outlier patterns, and mapping convergent changes toward a shared plan over time.

15. The system of claim 14, further comprising the steps of:

retrieving textual information from a query response;

scanning each query response for patterns of interest;

comparing one or more key components to data stored in a pattern library based upon past usage of the system;

comparing query responses with decision criteria data stored in a database;

classifying and linking patterns of interest into relational clusters; and

merging similar query responses, such that merged queries are stored and retrieved based on common search terms;

wherein concept-based retrieval is incorporated within Boolean search engines.

16. The system of claim 14, using an interactive, or rule-based, processor to annotate or tag text, wherein any electronic document, text-based or having a mix of graphics, audio, video, and/or pre-defined hypertext in addition to text, containing statements, indices, variables, decision points, recommendations, or other data, can be adapted for tagging.

17. The system of claim 14, wherein queries can be structured by the software to provide directed guidance to achieve a convergent result, bypassing roadblocks of conventional, consensus-driven collaborative process models by enabling discrete responders on the network to enter independent views, unconstrained by pressure for consensus from the group, such that iterative query structuring is automated or allows human judgment in implementing an iterative query system to converge toward a problem solution.