Abstract: Methods/systems receive a question and automatically search sources of data containing passages to produce candidate answers to the question. The searching identifies passages that support each of the candidate answers based on scoring features that indicate whether the candidate answers are correct answers to the question. These methods/systems automatically create a scoring feature-specific matrix for each scoring feature. Each scoring feature-specific matrix has a score field for each different combination of text passage and question term (vector), and each score field holds a score value (vector value) indicating how each different combination of text passage and question term supports the candidate answers as being a correct answer to the question. Next, such methods/systems automatically combine multiple such vectors to produce a combined vector score for each of the candidate answers, and then rank the candidate answers based on the combined scores.

Abstract: An approach to candidate answer generation by leveraging structural information in semi-structured resources, such as the title of a document and anchor texts in a document.

Abstract: A method of generating secondary questions in a question-answer system. Missing information is identified from a corpus of data using a computerized device. The missing information comprises any information that improves confidence scores for candidate answers to a question. The computerized device automatically generates a plurality of hypotheses concerning the missing information. The computerized device automatically generates at least one secondary question based on each of the plurality of hypotheses. The hypotheses are ranked based on relative utility to determine an order in which the computerized device outputs the at least one secondary question to external sources to obtain responses.

Abstract: A method of generating secondary questions in a question-answer system. Missing information is identified from a corpus of data using a computerized device. The missing information comprises any information that improves confidence scores for candidate answers to a question. The computerized device automatically generates a plurality of hypotheses concerning the missing information. The computerized device automatically generates at least one secondary question based on each of the plurality of hypotheses. The hypotheses are ranked based on relative utility to determine an order in which the computerized device outputs the at least one secondary question to external sources to obtain responses.

Abstract: A method of validating that a user is human. A user question is generated using a computerized device. The user question is output to a user. A user response to the user question is received from the user. The user response is validated as having been provided by a human.

Abstract: A computerized device for enhancing the accuracy of a question-answer system. The computerized device comprises a question-answer system comprising software for performing a plurality of question answering processes. A receiver receives a question into the question-answer system. A processor that generates a plurality of candidate answers to the question is connected to the question-answer system. The processor determines a confidence score for each of the plurality of candidate answers. The processor evaluates sources of evidence used to generate the plurality of candidate answers. The processor identifies missing information from a corpus of data. The missing information comprises any information that improves a confidence score for a candidate answer. The processor generates at least one follow-on inquiry based on the missing information. A network interface outputs the at least one follow-on inquiry to external sources separate from the question-answer system.

Abstract: A method of validating that a user is human. A user question is generated using a computerized device. The user question is output to a user. A user response to the user question is received from the user. The user response is validated as having been provided by a human.

Abstract: A method of enhancing the accuracy of a question-answer system. Missing information from a corpus of data is identified. The missing information is any information that improves a confidence for a candidate answer to a question. A follow-on inquiry is generated. The follow-on inquiry prompts for the missing information to be provided. The follow-on inquiry is output to an external source. A response to the follow-on inquiry is received from the external source. The response is added to the corpus of data.

Abstract: A method, system and computer program product for generating answers to questions. In one embodiment, the method comprises receiving a query, conducting a search through one or more data sources to identify candidate answers to the query, and providing each of the candidate answers with a preliminary score. The method further comprises filtering out any of the candidate answers with a preliminary score that does not satisfy a defined condition. The candidate answers having preliminary scores that satisfy this condition form a subset of the candidate answers. Each of the candidate answers in this subset is processed to produce further scores. A ranking function is applied to these further scores to determine a ranking for each of the candidate answers in the subset; and after this ranking function is applied, one or more of the candidate answers are selected as one or more final answers to the query.

Abstract: A method, system and computer program product for generating answers to questions. In one embodiment, the method comprises receiving an input query, identifying a plurality of candidate answers to the query; and for at least one of these candidate answers, identifying at least one proof of the answer. This proof includes a series of premises, and a multitude of documents are identified that include references to the premises. A set of these documents is selected that include references to all of the premises. This set of documents is used to generate one or more scores for the one of the candidate answers. A defined procedure is applied to the candidate answers to determine a ranking for the answers, and this includes using the one or more scores for the at least one of the candidate answers in the defined procedure to determine the ranking for this one candidate answer.

Abstract: Evidence profiling, in one aspect, may receive a candidate answer and supporting pieces of evidence. An evidence profile may be generated, the evidence profile communicating a degree to which the evidence supports the candidate answer as being correct. The evidence profile may provide dimensions of evidence, and each dimension may support or refute the candidate answer as being correct.

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 system, method and computer program product for efficiently retrieving relevant passages to questions based on a corpus of data. A processor device receives an input query and performs a query analysis to obtain searchable query terms. The processor performs: matching metadata associated with one or more documents against the query terms. The document metadata includes one or more of: a title of the documents, one or more user tags or clouds. Then the processor device performs: mapping matched document metadata to corresponding one or more documents; identifying corresponding matched documents to form a subcorpus of documents; and conducting a search in the data subcorpus using the searchable query terms to obtain one or more passages relevant input query from the identified documents.

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 are disclosed for searching for information using a knowledge base. In one embodiment, the method comprises receiving a query; formulizing the query, including dividing the query into a plurality of parts; for each of the parts, identifying a source, using the knowledge, that addresses that part; and combining the sources to answer the query. In one embodiment, the query includes text; the text is separated into a plurality of segments; and, for each of the segments, at least one source is identified addressing the segment. In an embodiment, a logical proof is formulated having a conclusion that is an answer to the query, and a sequence of statements that establish said conclusion; and a proof of this conclusion is generated by identifying two or more documents that assert the sequence of statements.

Abstract: Evidence profiling, in one aspect, may receive a candidate answer and supporting pieces of evidence. An evidence profile may be generated, the evidence profile communicating a degree to which the evidence supports the candidate answer as being correct. The evidence profile may provide dimensions of evidence, and each dimension may support or refute the candidate answer as being correct.

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, identifying a plurality of candidate answers to the query; and for at least one of these candidate answers, identifying at least one proof of the answer. This proof includes a series of premises, and a multitude of documents are identified that include references to the premises. A set of these documents is selected that include references to all of the premises. This set of documents is used to generate one or more scores for the one of the candidate answers. A defined procedure is applied to the candidate answers to determine a ranking for the answers, and this includes using the one or more scores for the at least one of the candidate answers in the defined procedure to determine the ranking for this one candidate answer.

Abstract: A method, system and computer program product for generating answers to questions. In one embodiment, the method comprises receiving a query, conducting a search through one or more data sources to identify candidate answers to the query, and providing each of the candidate answers with a preliminary score. The method further comprises filtering out any of the candidate answers with a preliminary score that does not satisfy a defined condition. The candidate answers having preliminary scores that satisfy this condition form a subset of the candidate answers. Each of the candidate answers in this subset is processed to produce further scores. A ranking function is applied to these further scores to determine a ranking for each of the candidate answers in the subset; and after this ranking function is applied, one or more of the candidate answers are selected as one or more final answers to the query.

Abstract: System, method and computer program product for 1) preparing queries for retrieving related content based on existing data content. For instance, titles of existing documents or entities extracted from documents can be used as queries. 2) Retrieving content from other repositories of unstructured, semi-structured, or structured data. For instance, web pages can be retrieved using existing search engines. 3) Extracting smaller units of text from the retrieved content. For instance, web pages can be split into coherent paragraphs of text. 4) Judging the quality of the smaller units of text and their relatedness to existing data. For instance, paragraphs can be scored using a statistical model based on lexico-syntactic features and topic models. 5) Synthesizing new sources from high-quality related text. For instance, paragraphs that score above a threshold can be concatenated into a new document.