Abstract: A question processing system routes questions among participants in a balanced and sustainable manner. Any participant can act as an inquirer (who poses questions) and an expert (who answers questions). In one illustrative case, the question processing system operates by: receiving a question from an inquirer; determining at least one expert that is appropriate to answer the question; and routing the question to the expert. The receiving, determining, and routing are repeated with respect to other inquirers and other experts to achieve a desired balance of information exchange among the plurality of participants of the electronic question processing system.

Abstract: Architecture for generating responses to search engine queries. Question/answer pairs are used to provide a predefined question hierarchy to facilitate a search. Informative terms and one or more questions are associated with each question node of the hierarchy. A question posed is mapped into the hierarchy to the most similar question class node, as determined by passages of the question and/or comparing the informative terms of the question and the question/answer node. Weighted informative terms associated with that node are then returned, and can be used by an automatic question answering system to more effectively find an answer to a question.

Abstract: Architecture is provided that facilitates user-controlled access to user profile information related to spam filtering. A user is allowed to selectively expose (or mask) portions of his/her profile related to spam filtering 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 profiles related to spam filtering. The architecture comprises a system that facilitates profile management utilizing a profile component that facilitates creation and storage of an electronic profile including spam filtering information of a user, and a control component under control of the user for controlling access to the profile.

Abstract: The present invention provides systems and methods that employ statistical filtering and ranking techniques to improve content search engine search results by tuning a general-purpose search engine for an entry point for a group of users. The filter can be manually and/or automatically configured via providing training sets of relevant and non-relevant data. For example, a relevant set of data comprising web pages associated with a desired search context for the group utilizing the entry point can be employed. In addition, a non-relevant set of data comprising random and unrelated documents can be employed. The learned filter can then be employed to compare a returned result with the known relevant and the known non-relevant data sets to determine whether the result is relevant to the user for the entry point, and the degree of relevance. The results can then be presented to the user based on the relevance.

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: 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: A context based search and document retrieval application is disclosed. The application uses context data that is generated by a document analysis component based upon context information from various sources, including for example, document collections available on the world wide web. The context data is provided to a search query generator. The search query generator is configured to generate a contextually annotated search query based upon a user query and context data. Bookmarks having an associated context are generated for documents retrieved in response to the contextually annotated search query. The application then provides access to the bookmarked documents when the user is browsing other documents with similar contexts to the context of the original document for which the context based search was executed and the bookmark created. The bookmarked documents are hyperlinked to terms in the browsed document.

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: A unique multi-stage classification system and method that facilitates reducing human resources or costs associated with text classification while still obtaining a desired level of accuracy is provided. The multi-stage classification system and method involve a pattern-based classifier and a machine learning classifier. The pattern-based classifier is trained on discriminative patterns as identified by humans rather than machines which allow a smaller training set to be employed. Given humans' superior abilities to reason over text, discriminative patterns can be more accurately and more readily identified by them. Unlabeled items can be initially processed by the pattern-based classifier and if no pattern match exists, then the unlabeled data can be processed by the machine learning classifier. By employing the classifiers in this manner, less human involvement is required in the classification process. Even more, classification accuracy is maintained and/or improved.

Abstract: The claimed subject matter provides systems and methods that facilitate providing specialized content associated with web results in response to a user query to provide queried information directly to a user without requiring the user to select a link and/or scroll through information on a web page associated therewith. Reference language models can be generated from multiple queries and can be compared to a query language model generated from web results returned in response to a user query. Based on such comparison, a determination can be made regarding whether a particular portion of specialized content corresponding to some particular query keywords is relevant enough to warrant direct presentation to the user.

Abstract: Structured content and associated metadata from the Web are leveraged to provide specific answer string responses to user questions. The structured content can also be indexed at crawl-time to facilitate searching of the content at search-time. Ranking techniques can also be employed to facilitate in providing an optimum answer string and/or a top K list of answer strings for a query. Ranking can be based on trainable algorithms that utilize feature vectors for candidate answer strings. In one instance, at crawl-time, structured content is indexed and automatically associated with metadata relating to the structured content and the source web page. At search-time, candidate indexed structured content is then utilized to extract an appropriate answer string in response to a user query.

Abstract: A system for associating information comprises an association module that uses anchoring information to associate a first piece of information with a second piece of information, wherein the second piece of information is not part of the first piece of information. The system further includes a rendering module that presents the second piece of information for use. Methods for using such a system are also described.

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: The subject invention relates to a system and/or methodology that facilitate converting structured data (e.g., tabular information) into natural language, thus making it available to question answering systems and search engines. More specifically, the system and method employ the vast quantities of natural language on the particular storage system, database, network, or server that a user wishes to search. For example, the system can utilize natural-language based information located on the Web to assist in the task of converting structured data into natural language. In particular, the system can find at least one sentence or sentence fragment on the Web that refers to at least one tuple (e.g., row) in a given table. Following, those sentences can be generalized across all or substantially all tuples in the table. The resulting body of text can be used by the question answering system to answer user queries.

Abstract: A unique ranking system and method that facilitates improving the ranking and ordering of objects to further enhance the quality, accuracy, and delivery of search results in response to a search query. The system and method involve monitoring and tracking an object in terms of the number of times it's been accessed and optionally by whom, when, for how long, and an access rate. The user's interaction with the object can be tracked as well. By tracking the objects, a popularity measure can be determined. Popularity based rankings can be computed based on the popularity measure or some function thereof. The popularity measure can be affected by the access time, who accessed it, access duration or the user's interaction with the object upon access. The popularity based rankings can be utilized by a search component to improve the quality and retrieval of search results.

Abstract: The present invention provides systems and methods that rank search results. Such ranking typically includes determining a relevance of individual search results via one or more feature-based relevance functions. These functions can be tailored to users and/or applications, and typically are based on scoped information (e.g., lexical), digital artifact author related attributes, digital artifact source repository attributes, and/or relationships between features, for example. In addition, relevance functions can be generated via training sets (e.g., machine learning) or initial guesses that are iteratively refined over time. Upon determining relevance, search results can be ordered with respect to one another, based on respective relevances. Additionally, thresholding can be utilized to mitigate returning results likely to be non-relevant to the query, user and/or application.

Abstract: The present invention relates to a system and methodology to facilitate extraction of information from a large unstructured corpora such as from the World Wide Web and/or other unstructured sources. Information in the form of answers to questions can be automatically composed from such sources via probabilistic models and cost-benefit analyses to guide resource-intensive information-extraction procedures employed by a knowledge-based question answering system. The analyses can leverage predictions of the ultimate quality of answers generated by the system provided by Bayesian or other statistical models. Such predictions, when coupled with a utility model can provide the system with the ability to make decisions about the number of queries issued to a search engine (or engines), given the cost of queries and the expected value of query results in refining an ultimate answer. Given a preference model, information extraction actions can be taken with the highest expected utility.

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 present invention leverages relevance data to provide enhanced search query results based on relevancy to a specific entity via an entity-specific tunable search. This allows an entity to retrieve information that is of more value to that entity, in a faster and more efficient manner. The entity itself can be an individual user, a grouping of users, and/or an enterprise and the like. In one instance of the present invention, entity-specific relevance information is determined via employment of similarity of the entity to another entity or group of entities. Interest levels and/or satisfaction levels of similar entities can also be utilized along with similarity information to facilitate in deriving the relevance information.