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: A method, system, and computer-accessible medium are provided for automating the optimization of search result relevance in a search engine. The system and method continually collect data that represent various aspects of how a search result is performing and compare that performance data to the expected performance for the search result. The system and method further diagnose the possible causes of under performing results and automatically adjust the search engine operation to optimize the search result relevance.

Abstract: Computer users may integrate any annotation, including ink, highlighter, text-based notes and audio, directly into a Web-based document (WBD) displayed by a Web browser. This integration enables others to view the personalized annotated WBD, which retains its original active links and properties, over the Internet without the need for specialized software. Annotations are integrated into WBDs by freezing the WBD, overlaying an image file containing the annotations onto the WBD, and enabling browser events to pass through the image layer. Annotations may also be integrated into WBDs by using component object technology. By collecting and organizing annotated WBDs, users can be provided with an intuitive Web-based interface for accessing, viewing and searching the annotated WBDs. Users may annotate blank WBDs, effectively converting their Web browsers into online notebooks/scrapbooks.

Abstract: Rating information retrieval algorithms. A query is received and submitted to a search engine for execution on an index file. A list of index documents and a plurality of attributes are received from the search engine in response to the submitted query. A portion of the received list of index documents and the received plurality of attributes are stored in a subindex file. The received query is executed on the subindex file to obtain a list of subindex documents. The obtained list of subindex documents is ranked by a particular ranking algorithm using the attributes associated therewith. The list of ranked subindex documents is compared with a list of subjectively ranked documents to generate a score for the particular ranking algorithm. The generated score represents a degree of correlation between the list of ranked subindex documents and the list of subjectively ranked documents.

Abstract: A system, method, and computer-accessible medium for a unified search of disparate resources are provided. The system and method determine the most relevant disparate resources in which to search and blend the most relevant results from the search for presentation to the user in an integrated manner.

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: A system that employs an explicitly and/or implicitly trained model in order to return entity-specific computer-based search results is provided. The innovation can provide for a customized search model that focuses search in connection with achieving information that is meaningful with respect to goals of an entity. The model can be used to modify a search query in accordance with a goal of the entity or to generate the search query thereby returning meaningful and/or targeted results to the user. The system can automatically gather entity-related data thereafter determining or inferring a goal as well as training the model. Moreover, the system can selectively configure (e.g., order, rank, filter) and render results to a user based upon the model.

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: A system that employs an explicitly and/or implicitly trained model in order to return entity-specific computer-based search results is provided. The innovation can provide for a customized search model that focuses search in connection with achieving information that is meaningful with respect to goals of an entity. The model can be used to modify a search query in accordance with a goal of the entity or to generate the search query thereby returning meaningful and/or targeted results to the user. The system can automatically gather entity-related data thereafter determining or inferring a goal as well as training the model. Moreover, the system can selectively configure (e.g., order, rank, filter) and render results to a user based upon the model.

Abstract: Provided is mechanism for guiding computer searches (e.g. web, Internet, intranet . . . ). Machine learning and reasoning mechanisms are employed together with a search engine to facilitate intelligent guidance of queries and results based on a query and responses to computer generated inquires. Also, disclosed is a mechanism that enables users to validate computer-based information. Users can receive a validity metric associated with computer generated or provided results indicative of the veracity of such results. Validation systems and methods are disclosed to facilitate determining the veracity of results including those that employ humans (e.g., referrals, voting . . . ) and/or automated means (e.g. source analysis, data mining. . . ).

Abstract: A system that can analyze a multi-dimensional input thereafter establishing a search query based upon extracted features from the input. In a particular example, an image can be used as an input to a search mechanism. Pattern recognition and image analysis can be applied to the image thereafter establishing a search query that corresponds to features extracted from the image input. The system can also facilitate indexing multi-dimensional searchable items thereby making them available to be retrieved as results to a search query. More particularly, the system can employ text analysis, pattern and/or speech recognition mechanisms to extract features from searchable items. These extracted features can be employed to index the searchable items.

Abstract: The subject disclosure pertains to scrutinizing results generated or otherwise provided by a computer. A mechanism is provided that enables users to validate computer-based information. Users can receive a validity metric associated with computer generated or provided results indicative of the veracity of such results. Validation systems and methods are disclosed to facilitate determining the veracity of results including those that employ humans (e.g., referrals, voting . . . ) and/or automated means (e.g., source analysis, data mining . . . ). The disclosure also provides a mechanism for guiding computer searches (e.g., web, Internet, intranet . . . ). Machine learning and reasoning mechanisms are employed together with a search engine to facilitate intelligent guidance of queries and results based on a query and responses to computer generated inquires.

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: The innovation provides for a computer search to become an action that has direct nexus to an inferred (or determined) goal of an individual. The goal can be inferred or determined from any number of context/state factors. The innovation can query a user to determine user context and state factors by which a goal, objective or intent can be automatically established. The innovation can also utilize machine learning/reasoning to establish the goal of a user based upon historical, statistical and/or other probabilistic analysis. Still further, the innovation can monitor a user's context and state thereafter dynamically journaling and logging the criterion by which the user's objective(s) can be established. Once a goal is established, a goal-based search can be automatically conducted thereafter prompting for an action based upon a subset of the search 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: 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).