Abstract: Context-based disambiguation of acronyms and/or abbreviations may determine a target abbreviation and one or more keywords appearing in context with the target abbreviation in a received passage, the target abbreviation representing a shortened form of one or more word. A contextual search query including the target abbreviation and said one or more keywords may be generated. A pseudo document index may be searched for one or more expansions of the target abbreviation by invoking the contextual search query, the pseudo document index containing index of one or more pseudo documents, associated one or more abbreviations and associated context keywords. One or more pseudo documents associated with the target abbreviation may be returned based on the searching of the pseudo document index.

Abstract: Context-based disambiguation of acronyms and/or abbreviations may determine a target abbreviation and one or more keywords appearing in context with the target abbreviation in a received passage, the target abbreviation representing a shortened form of one or more word. A contextual search query including the target abbreviation and said one or more keywords may be generated. A pseudo document index may be searched for one or more expansions of the target abbreviation by invoking the contextual search query, the pseudo document index containing index of one or more pseudo documents, associated one or more abbreviations and associated context keywords. One or more pseudo documents associated with the target abbreviation may be returned based on the searching of the pseudo document index.

Abstract: A method, system and computer program product for generating answers to questions. In one embodiment, the method comprises receiving an input query, decomposing the input query into a plurality of different subqueries, and conducting a search in one or more data sources to identify at least one candidate answer to each of the subqueries. A ranking function is applied to each of the candidate answers to determine a ranking for each of these candidate answers; and for each of the subqueries, one of the candidate answers to the subquery is selected based on this ranking. A logical synthesis component is applied to synthesize a candidate answer for the input query from the selected the candidate answers to the subqueries. In one embodiment, the procedure applied by the logical synthesis component to synthesize the candidate answer for the input query is determined from the input query.

Abstract: A method, system and computer program product for generating answers to questions. In one embodiment, the method comprises receiving an input query, decomposing the input query into a plurality of different subqueries, and conducting a search in one or more data sources to identify at least one candidate answer to each of the subqueries. A ranking function is applied to each of the candidate answers to determine a ranking for each of these candidate answers; and for each of the subqueries, one of the candidate answers to the subquery is selected based on this ranking. A logical synthesis component is applied to synthesize a candidate answer for the input query from the selected the candidate answers to the subqueries. In one embodiment, the procedure applied by the logical synthesis component to synthesize the candidate answer for the input query is determined from the input query.

Abstract: Mechanisms are provided for generating a dictionary data structure for analytical operations. A source terminology resource is ingested to generate a hierarchical representation of the source terminology resource comprising nodes for terms related to concepts in the source terminology resource. For a node of the nodes in the hierarchical representation of the source terminology resource, a permutation of a corresponding term associated with the node is generated. An expanded hierarchical representation of the source terminology resource is generated based on the generated permutation. An enhanced dictionary data structure is generated based on the expanded hierarchical representation and output to an analytics engine to perform analysis of a corpus of information using the enhanced dictionary data structure.

Abstract: Automated question answering is disclosed that relates to the selection of an answer to a question from a pool of potential answers which are manually or automatically extracted from a large collection of textual documents. The a feature extraction component, a feature combination component, an answer selection component, and an answer presentation component, among others, are included. The input to the system is a set of one or more natural language questions and a collection of textual document. The output is a (possibly ranked) set of factual answers to the questions, these answers being extracted from the document collection.

Abstract: A method, system and computer program product for generating answers to questions. In one embodiment, the method comprises receiving an input query, decomposing the input query into a plurality of different subqueries, and conducting a search in one or more data sources to identify at least one candidate answer to each of the subqueries. A ranking function is applied to each of the candidate answers to determine a ranking for each of these candidate answers; and for each of the subqueries, one of the candidate answers to the subquery is selected based on this ranking. A logical synthesis component is applied to synthesize a candidate answer for the input query from the selected the candidate answers to the subqueries. In one embodiment, the procedure applied by the logical synthesis component to synthesize the candidate answer for the input query is determined from the input query.

Abstract: Context-based disambiguation of acronyms and/or abbreviations may determine a target abbreviation and one or more keywords appearing in context with the target abbreviation in a received passage, the target abbreviation representing a shortened form of one or more word. A contextual search query including the target abbreviation and said one or more keywords may be generated. A pseudo document index may be searched for one or more expansions of the target abbreviation by invoking the contextual search query, the pseudo document index containing index of one or more pseudo documents, associated one or more abbreviations and associated context keywords. One or more pseudo documents associated with the target abbreviation may be returned based on the searching of the pseudo document index.

Abstract: Context-based disambiguation of acronyms and/or abbreviations may determine a target abbreviation and one or more keywords appearing in context with the target abbreviation in a received passage, the target abbreviation representing a shortened form of one or more word. A contextual search query including the target abbreviation and said one or more keywords may be generated. A pseudo document index may be searched for one or more expansions of the target abbreviation by invoking the contextual search query, the pseudo document index containing index of one or more pseudo documents, associated one or more abbreviations and associated context keywords. One or more pseudo documents associated with the target abbreviation may be returned based on the searching of the pseudo document index.

Abstract: A method, system and computer program product for generating answers to questions. In one embodiment, the method comprises receiving an input query, decomposing the input query into a plurality of different subqueries, and conducting a search in one or more data sources to identify at least one candidate answer to each of the subqueries. A ranking function is applied to each of the candidate answers to determine a ranking for each of these candidate answers; and for each of the subqueries, one of the candidate answers to the subquery is selected based on this ranking. A logical synthesis component is applied to synthesize a candidate answer for the input query from the selected the candidate answers to the subqueries. In one embodiment, the procedure applied by the logical synthesis component to synthesize the candidate answer for the input query is determined from the input query.

Abstract: A computer includes a data/knowledge base with a plurality of entries and further employs a user/computer interface for responding to a natural language form input. The interface, in combination with the computer, provides a help function that includes a browse search capability that responds to the natural language-form input by responding with matching knowledge base data.

Abstract: A user/computer interface is described that employ a constrained natural language-form input. The computer employs a feedback method to reinforce a user's confidence and knowledge that the computer comprehends a query or instruction. The user interface initially parses a user's natural language-form input into a case frame. The case frame is then filtered into a goal-expression that comprises a verb and remaining syntactical portions of the input query/instruction. The system then paraphrases the goal-expression into constrained natural language-form and communicates the paraphrase to the user for confirmation that the computer system has correctly interpreted the user input. The computer also compares the goal-expression with prestored goal-expressions to determine a match and then performs an action in response to a match being found.

Abstract: A data processing system which suggests a valid command to a user when the user enters a question or an erroneous command. The purposes of the various commands executable by the system are stored as a plurality of intents. When the user enters a question or an erroneous command, the system looks up the intent corresponding to it and semantically compares such an intent with other intents. When another intent is found, based on the comparison, to be within a predetermined degree of similarity, the command defined by such other intent is offered as a suggestion to the user.

Abstract: A data processing includes an on-line, interactive, intelligent help system which provides suggestions as to actions a user can take after entry into the system of an erroneous command or a question. The system also responds with explanations of why the suggestions were made and how they work. The system includes a natural language analyzer for converting the questions into goals. A knowledge base and an inference engine further analyze the goals and provide one or more suggestions on how to achieve such goals. An explanation generator uses such analysis to dynamically generate the explanations which are tailored to the user's goal.