Abstract: Architecture for completing search queries by using artificial intelligence based schemes to infer search intentions of users. Partial queries are completed dynamically in real time. Additionally, search aliasing can also be employed. Custom tuning can be performed based on at least query inputs in the form of text, graffiti, images, handwriting, voice, audio, and video signals. Natural language processing occurs, along with handwriting recognition and slang recognition. The system includes a classifier that receives a partial query as input, accesses a query database based on contents of the query input, and infers an intended search goal from query information stored on the query database. A query formulation engine receives search information associated with the intended search goal and generates a completed formal query for execution.

Abstract: Architecture for completing search queries by using artificial intelligence based schemes to infer search intentions of users. Partial queries are completed dynamically in real time. Additionally, search aliasing can also be employed. Custom tuning can be performed based on at least query inputs in the form of text, graffiti, images, handwriting, voice, audio, and video signals. Natural language processing occurs, along with handwriting recognition and slang recognition. The system includes a classifier that receives a partial query as input, accesses a query database based on contents of the query input, and infers an intended search goal from query information stored on the query database. A query formulation engine receives search information associated with the intended search goal and generates a completed formal query for execution.

Abstract: A wireless communication system that concurrently communicates information in multiple regulatory domains to facilitate audio/video media streaming and other high bandwidth operations. One domain may be licensed and the other may be unlicensed. Transmission in the licensed domain may occur in white space in the domain, and the amount of information transmitted in that domain may be limited by regulations. The amount of information conveyed in the licensed domain may also depend on channel conditions in either or both of the domains. As a result, the relative amount of to information transmitted in each domain may vary dynamically. The system includes a transmitter that dynamically determines weighting coefficients applied to each of a plurality of channels to set power levels in both domains to achieve a desired metric for the overall communication. A corresponding receiver assembles the substreams into a stream that can then be displayed or otherwise processed.

Abstract: Architecture for completing search queries by using artificial intelligence based schemes to infer search intentions of users. Partial queries are completed dynamically in real time. Additionally, search aliasing can also be employed. Custom tuning can be performed based on at least query inputs in the form of text, graffiti, images, handwriting, voice, audio, and video signals. Natural language processing occurs, along with handwriting recognition and slang recognition. The system includes a classifier that receives a partial query as input, accesses a query database based on contents of the query input, and infers an intended search goal from query information stored on the query database. A query formulation engine receives search information associated with the intended search goal and generates a completed formal query for execution.

Abstract: Architecture is provided that facilitates user-controlled access to user profile information. A user is allowed to selectively expose (or mask) portions of his/her profile to third parties. Additionally, advertisers and/or content providers can offer incentives or enticement in response to the acceptance of which a user exposes larger portions of their profile. The architecture comprises a system that facilitates profile management utilizing a profile component that facilitates creation and storage of an electronic profile of a user, and a control component under control of the user for controlling access to the profile. Machine learning and reasoning is provided to make inferences and automate aspects thereof.

Abstract: Architecture is provided that facilitates user-controlled access to user profile information. A user is allowed to selectively expose (or mask) portions of his/her profile to third parties. Additionally, advertisers and/or content providers can offer incentives or enticement in response to the acceptance of which a user exposes larger portions of their profile. The architecture comprises a system that facilitates profile management utilizing a profile component that facilitates creation and storage of an electronic profile of a user, and a control component under control of the user for controlling access to the profile. Machine learning and reasoning is provided to make inferences and automate aspects thereof.

Abstract: Content management architecture for a portable wireless device. Caching and fetching techniques are provided to improve content handling for portable devices such as cellular telephones and portable computers. A search component automatically performs searches as a background process, and potentially desired content is received and cached by a content storing component to be available in the future when and if needed, mitigating latency associated with slow download speeds, refresh rates, and other system and/or network impediments. Content from background search results can be trickled into the device as part of the background process so as not to burden system resources for other processes. As part of memory management, aged and/or low priority or low interest content can be selectively removed or archived to increase available cache or memory space, as well as to maintain relevant content within the device. A presentation component facilitates presentation of the pre-stored content.

Abstract: Architecture is provided that facilitates user-controlled access to user profile information. A user is allowed to selectively expose (or mask) portions of his/her profile to third parties. Additionally, advertisers and/or content providers can offer incentives or enticement in response to the acceptance of which a user exposes larger portions of their profile. The architecture comprises a system that facilitates profile management utilizing a profile component that facilitates creation and storage of an electronic profile of a user, and a control component under control of the user for controlling access to the profile. Machine learning and reasoning is provided to make inferences and automate aspects thereof.

Abstract: Architecture for completing search queries by using artificial intelligence based schemes to infer search intentions of users. Partial queries are completed dynamically in real time. Additionally, search aliasing can also be employed. Custom tuning can be performed based on at least query inputs in the form of text, graffiti, images, handwriting, voice, audio, and video signals. Natural language processing occurs, along with handwriting recognition and slang recognition. The system includes a classifier that receives a partial query as input, accesses a query database based on contents of the query input, and infers an intended search goal from query information stored on the query database. A query formulation engine receives search information associated with the intended search goal and generates a completed formal query for execution.

Abstract: Architecture for completing search queries by using artificial intelligence based schemes to infer search intentions of users. Partial queries are completed dynamically in real time. Additionally, search aliasing can also be employed. Custom tuning can be performed based on at least query inputs in the form of text, graffiti, images, handwriting, voice, audio, and video signals. Natural language processing occurs, along with handwriting recognition and slang recognition. The system includes a classifier that receives a partial query as input, accesses a query database based on contents of the query input, and infers an intended search goal from query information stored on the query database. A query formulation engine receives search information associated with the intended search goal and generates a completed formal query for execution.

Abstract: Architecture for completing search queries by using artificial intelligence based schemes to infer search intentions of users. Partial queries are completed dynamically in real time. Additionally, search aliasing can also be employed. Custom tuning can be performed based on at least query inputs in the form of text, graffiti, images, handwriting, voice, audio, and video signals. Natural language processing occurs, along with handwriting recognition and slang recognition. The system includes a classifier that receives a partial query as input, accesses a query database based on contents of the query input, and infers an intended search goal from query information stored on the query database. A query formulation engine receives search information associated with the intended search goal and generates a completed formal query for execution.

Abstract: Architecture is provided that facilitates user-controlled access to user profile information. A user is allowed to selectively expose (or mask) portions of his/her profile to third parties. Additionally, advertisers and/or content providers can offer incentives or enticement in response to the acceptance of which a user exposes larger portions of their profile. The architecture comprises a system that facilitates profile management utilizing a profile component that facilitates creation and storage of an electronic profile of a user, and a control component under control of the user for controlling access to the profile. Machine learning and reasoning is provided to make inferences and automate aspects thereof.

Abstract: Architecture for presenting advertisements in realtime in retail establishments. A sensor component includes sensors for collecting information about a customer or group of customers as they move through the store. The sensors can include capability for image processing, audio processing, light sensing, velocity sensing, direction sensing, proximity sensing, face recognition, pose recognition, transaction recognition, and biometric sensing, for example. A customer component analyzes the information and generates a profile about the customer. Advertisements are selected for presentation that target the customers as they walk in proximity of a presentation system of the store. An advertisement component facilitates dynamic presentation of a targeted advertisement to the individual as a function of the profile. The customer component can infer information during analysis using machine learning and reasoning.

Abstract: The subject disclosure pertains to web searches and more particularly toward influencing resultant content to increase relevancy. The resultant content can be influenced by reconfiguring a query and/or filtering results based on user location and/or context information (e.g., user characteristics/profile, prior interaction/usage temporal, current events, and third party state/context . . . ). Furthermore, the disclosure provides for query execution on at least a subset of designated web content, for example as specified by a user. Still further yet, a localized marketing system is disclosed that provides discount offers to users that match merchant criteria including proximity. A system for actively probing populations of users with different parameters and monitoring responses can be employed to collect data for identifying the best discounts and deadlines to offer to users to achieve desired results.

Abstract: A system that incorporates a user context into a computer-based search is provided. To establish the context, the innovation can identify information about a user state or context via a variety of sources and sensors. The state/context information can be used to filter, arrange and/or rank search results so as to facilitate converging on meaningful searches and results. Machine learning systems (implicitly and/or explicitly trained) can be employed to infer a current and/or future context related to user. An identified or inferred user context can be employed to modify an automated or user-defined search input/query. Contextual cues can be considered directly in the construction and use of context of context-sensitive retrieval algorithms that are optimized for identifying and/or ranking of informational items of potential interest or value in different contexts. As well, the context can be employed to intelligently render results of a query (e.g., user/application defined, context-modified query).

Abstract: The subject disclosure pertains to web searches and more particularly toward influencing resultant content to increase relevancy. The resultant content can be influenced by reconfiguring a query and/or filtering results based on user location and/or context information (e.g., user characteristics/profile, prior interaction/usage temporal, current events, and third party state/context . . . ). Furthermore, the disclosure provides for query execution on at least a subset of designated web content, for example as specified by a user. Still further yet, a localized marketing system is disclosed that provides discount offers to users that match merchant criteria including proximity. A system for actively probing populations of users with different parameters and monitoring responses can be employed to collect data for identifying the best discounts and deadlines to offer to users to achieve desired results.

Abstract: Architecture is provided that facilitates user-controlled access to user profile information. A user is allowed to selectively expose (or mask) portions of his/her profile to third parties. Additionally, advertisers and/or content providers can offer incentives or enticement in response to the acceptance of which a user exposes larger portions of their profile. The architecture comprises a system that facilitates profile management utilizing a profile component that facilitates creation and storage of an electronic profile of a user, and a control component under control of the user for controlling access to the profile. Machine learning and reasoning is provided to make inferences and automate aspects thereof.

Abstract: Architecture for targeted advertising using offline user behavior information. Information relating to offline behavior can be collected from cell phones, geolocation systems, credit card information, restaurants, grocery stores, etc., and this information is aggregated and employed in connection with selecting and displaying targeted advertising to a user when online. Machine learning and reasoning can be employed to make inferences and dynamically tune advertisement processing. Offline user information can also be employed to enhance context-based searching when the user goes online. The ranking of search results and content for display can be modified as a function of offline behavior. A system is provided that facilitates online advertising based on at least offline activity using a profile component for aggregating offline behavior information of a user and generating a related user profile.

Abstract: Architecture that monitors interaction data (e.g., search queries, query results and click-through rates), and provides users with links to other users that fall into similar categories with respect to the foregoing monitored activities (e.g., providing links to individuals and groups that share common interests and/or profiles). A search engine can be interactively coupled with one or more social networks, and that maps individuals and/or groups within respective social networks to subsets of categories associated with searches. A database stores mapped information which can be continuously updated and reorganized as links within the system mapping become stronger or weaker. The architecture can comprise a social network system that includes a database for mapping search-related information to an entity of a social network, and a search component for processing a search query for search results and returning a link to an entity of a social network based on the search query.

Abstract: Architecture for targeted advertising using offline user behavior information. Information relating to offline behavior can be collected from cell phones, geolocation systems, credit card information, restaurants, grocery stores, etc., and this information is aggregated and employed in connection with selecting and displaying targeted advertising to a user when online. Machine learning and reasoning can be employed to make inferences and dynamically tune advertisement processing. Offline user information can also be employed to enhance context-based searching when the user goes online. The ranking of search results and content for display can be modified as a function of offline behavior. A system is provided that facilitates online advertising based on at least offline activity using a profile component for aggregating offline behavior information of a user and generating a related user profile.