Abstract: The present invention relates to a method to make effective use of display space. In an embodiment of the invention, given a heterogeneous set of images along with metadata or nearby text, similar images are recursively clustered into a k-tree using the k-means algorithm. In an embodiment of the invention, the invention is particularly useful for showing image search results on small mobile devices.

Abstract: Techniques are provided to determine service data features from an archive of web service transactions. Data features for functionally identical classes of service are determined. Differentiating data feature patterns uniquely identifying each service within the class are learned using machine learning, clustering, statistical analysis and the like. A service map associating services with the differentiating patterns is determined. The service map contains data feature patterns that differentiate among otherwise functionally identical services. The data features are optionally associated with past usage, objective and subjective service quality measurements and the like. The data features of the received service requests are compared to differentiating patterns in the service map. The service associated with the differentiating patterns matching the data features of the service request is selected.

Abstract: Techniques are provided for segmenting text into categorized discourse constituents and attaching discourse constituents into a structural representation of discourse. Techniques for determining hybrid structural and non-structural summaries of a text are also provided. A text is segmented based on a theory of discourse analysis into at least a main discourse constituent containing spatio-temporal information about a single event in a possible world view. The discourse constituents are then inserted into a structural representation of discourse. Non-structural techniques are used to determine relevance scores and important discourse constituents are determined. Relevance scores are percolated through the structural representation of discourse to determine supporting preceding discourse constituents that preserve grammaticality. A hybrid text summary is then determined based on the structural representation of the discourse and relevance scores.

Abstract: Techniques are provided for determining collaborative notes and automatically recognizing speech, handwriting and other type of information. Domain and optional actor/speaker information associated with the support information is determined. An initial automatic speech recognition model is determined based on the domain and/or actor information. The domain and/or actor/speaker language model is used to recognize text in the speech information associated with the support information. Presentation support information such as slides, speaker notes and the like are determined. The semantic overlap between the support information and the salient non-function words in the recognized text and collaborative user feedback information are used to determine relevancy scores for the recognized text. Grammaticality, well formedness, self referential integrity and other features are used to determine correctness scores.

Abstract: Techniques are provided for determining collaborative notes and automatically recognizing speech, handwriting and other type of information. Domain and optional actor/speaker information associated with the support information is determined. An initial automatic speech recognition model is determined based on the domain and/or actor information. The domain and/or actor/speaker language model is used to recognize text in the speech information associated with the support information. Presentation support information such as slides, speaker notes and the like are determined. The semantic overlap between the support information and the salient non-function words in the recognized text and collaborative user feedback information are used to determine relevancy scores for the recognized text. Grammaticality, well formedness, self referential integrity and other features are used to determine correctness scores.

Abstract: Technologies are described herein for generating a semantic translation rule to support natural language search. In one method, a first expression and a second expression are received. A first representation is generated based on the first expression, and a second representation is generated based on the second expression. Aligned pairs of a first term in the first representation and a second term in the second representation are determined. For each aligned pair, the first term and the second term are replaced with a variable associated with the aligned pair. Word facts that occur in both the first representation and the second representation are removed from the first representation and the second representation. The remaining word facts in the first representation are replaced with a broader representation of the word facts. The translation rule including the first representation, an operator, and the second semantic representation is generated.

Abstract: A role tree having nodes corresponding to semantic roles in a hierarchy is defined. A posting list is generated for each association of a term and a semantic role in the hierarchy. The posting lists are stored contiguously on a physical storage medium such that a subtree of the hierarchy of semantic roles can be loaded from the storage medium as a single contiguous block. The posting lists for a subtree of the hierarchy are retrieved by obtaining data identifying the beginning location on the physical storage medium of the posting lists for the term at the top of a desired subtree of the hierarchy and data identifying the length of the posting lists of the desired subtree of the hierarchy. A single contiguous block that includes the posting lists for the desired subtree of the hierarchy is then retrieved from the beginning location through the specified length.

Abstract: Word sense probabilities are compressed for storage in a semantic index. Each word sense for a word is mapped to one of a number of “buckets” by assigning a bucket score to the word sense. A scoring function is utilized to assign the bucket scores that maximizes the entropy of the assigned bucket scores. Once the bucket scores have been assigned to the word senses, the bucket scores are stored in the semantic index. The bucket scores stored in the semantic index may be utilized to prune one or more of the word senses prior to construction of the semantic index. The bucket scores may also be utilized to prune and rank the word senses at the time a query is performed using the semantic index.

Abstract: Technologies are described herein for coreference resolution in an ambiguity-sensitive natural language processing system. Techniques for integrating reference resolution functionality into a natural language processing system can processes documents to be indexed within an information search and retrieval system. Ambiguity awareness features, as well as ambiguity resolution functionality, can operate in coordination with coreference resolution. Annotation of coreference entities, as well as ambiguous interpretations, can be supported by in-line markup within text content or by external entity maps. Information expressed within documents can be formally organized in terms of facts, or relationships between entities in the text. Expansion can support applying multiple aliases, or ambiguities, to an entity being indexed so that all of the possibly references or interpretations for that entity are captured into the index.

Abstract: Tools and techniques are described that relate to iterators for applying term occurrence-level constraints in natural language searching. These tools may receive a natural language input query, and define term occurrence-level constraints applicable to the input query. The methods may also identify facts requested in the input query, and may instantiate an iterator to traverse a fact index to identify candidate facts responsive to the input query. This iterator may traverse through at least a portion of the fact index. The methods may receive candidate facts from this iterator, with these candidate facts including terms, referred to as term-level occurrences. The methods may apply the term occurrence-level constraints to the term-level occurrences. The methods may select the candidate fact for inclusion in search results for the input query, based at least in part on applying the term occurrence-level constraint.

Abstract: Computer-readable media and computer systems for conducting semantic processes to facilitate navigation of search results that include sets of tuples representing facts associated with content of documents in response to queries for information. Content of documents is accessed and semantic structures are derived by distilling linguistic representations from the content. Groups of two or more related words, called tuples, are extracted from the documents or the semantic structures. Tuples can be stored at a tuple index. Representations of the relational tuples are displayed in addition to documents retrieved in response to a query.

Abstract: Computer-readable media, computerized methods, and computer systems for conducting semantic processes to present search results that include highlighted regions which are relevant to a conceptual meaning of a query are provided. Initially, content of document(s) is accessed and semantic representations are derived by distilling linguistic representations from the content. These semantic representations may be stored at a semantic index. Also, a proposition is derived from the query by parsing search terms of the query, and distilling the proposition from the search terms. Typically, the proposition is a logical representation of the conceptual meaning of the query. The proposition is compared against the semantic representations at the semantic index to identify a matching set. Regions of the content within the document, from which the matching set of semantic representations are derived, are targeted.

Abstract: Computer-readable media and a computer system for implementing a natural language search using fact-based structures and for generating such fact-based structures are provided. A fact-based structure is generated using a semantic structure, which represents information, such as text, from a document, such as a web page. Typically, a natural language parser is used to create a semantic structure of the information, and the parser identifies terms, as well as the relationship between the terms. A fact-based structure of a semantic structure allows for a linear structure of these terms and their relationships to be created, while also maintaining identifiers of the terms to convey the dependency of one fact-based structure on another fact-based structure. Additionally, synonyms and hypernyms are identified while generating the fact-based structure to improve the accuracy of the overall search.

Abstract: Methods and computer-readable media for associating words or groups of words distilled from content, such as reported speech or an attitude report, of a document to form semantic relationships collectively used to generate a semantic representation of the content are provided. Semantic representations may include elements identified or parsed from a text portion of the content, the elements of which may be associated with other elements that share a semantic relationship, such as an agent, location, or topic relationship. Relationships may also be developed by associating one element that is in relation to, or is about, another element, thereby allowing for rapid and effective comparison of associations found in a semantic representation with associations derived from queries. The semantic relationships may be determined based on semantic information, such as potential meanings and grammatical functions of each element within the text portion of the content.

Abstract: A system for providing a dynamic audio-visual environment using an eSurface situated in a room environment; a projector situated for projecting images onto the eSurface; a camera situated to picture the room environment; a central processor coupled to the eSurface, the projector and the camera. The processor receives pictures from the camera for detecting the location of the eSurface; and controls the projector to aim its projection beam onto the eSurface. The eSurface is a sheet-like surface having the property of accepting optically projected image when powered, and retaining the projected image after the power is turned off.

Abstract: The present invention relates to a method to make effective use of display space. In an embodiment of the invention, given a heterogeneous set of images along with metadata or nearby text, similar images are recursively clustered into a k-tree using the k-means algorithm. In an embodiment of the invention, the invention is particularly useful for showing image search results on small mobile devices.