Abstract: A system, method and computer program product for conducting questions and answers with deferred type evaluation based on any corpus of data. The method includes processing a query including waiting until a “Type” (i.e. a descriptor) is determined AND a candidate answer is provided. Then, a search is conducted to look (search) for evidence that the candidate answer has the required Lexical Answer Type (e.g., as determined by a matching function that can leverage a parser, a semantic interpreter and/or a simple pattern matcher). Prior to or during candidate answer evaluation, a process is provided for extracting and storing collections of entity-type pairs from semi-structured text documents. During QA processing and candidate answer scoring, a process is implemented to match the query LAT against the lexical type of each provided candidate answer and generate a score judging a degree of match.

Abstract: This invention defines a method and system for benchmarking an entity's innovation or research and development strategy (represented by a collection of documents) against a collection of documents or corpus that defines the future direction of an industry sector; a future technology or research and development roadmap; or the innovation strategy or research and development strategy of another entity; where an entity could be a corporation, a government, a country, an industry sector, a competitor, or a projected technology future scenario. This invention identifies and uses implicit technology concepts to benchmark the innovation strategy or research and development strategy of one entity to a future technology roadmap or to the innovation strategy of another entity. These implicit technology concepts are used to build relationship data tables that define the links between entities, identify the overlaps and gaps between entities, and benchmark multiple entities.

Abstract: According to an aspect, a heterogeneous graph in a data store is accessed. The heterogeneous graph includes a plurality of nodes having a plurality of node types. The nodes are connected by edges having a plurality of relation types. One or more intermediary graphs are created based on the heterogeneous graph. The intermediary graphs include intermediary nodes that are the relation types of the edges of the heterogeneous graph and include intermediary links between the intermediary nodes based on shared instances of the nodes between relation types in the heterogeneous graph. The intermediary graphs are traversed to find sets of relations based on intermediary links according to a template. An inference rule is extracted from the heterogeneous graph based on finding sets of relations in the intermediary graphs. The inference rule defines an inferred relation type between at least two of the nodes of the heterogeneous graph.

Abstract: The present disclosure relates generally to question answering systems and methods and, particularly, to systems and methods for domain adaptation in question answering.

Abstract: A question/answer creation system is described. The system includes a memory device and a processor connected to the memory device. The processor is configured to import a document having a set of questions based on content in the document, automatically create a candidate question from the content in the document, automatically generate answers for the set of questions and the candidate question using the content in the document, present the set of questions, the candidate question, and the answers to a content creator for user verification of accuracy, and store a verified set of questions in the document. The verified set of questions includes at least one verified question from the set of questions and the candidate question.

Abstract: A method for question/answer creation for a document is described. The method includes importing a document having a set of questions based on content in the document. The method also includes automatically creating a candidate question from the content in the document. The method also includes automatically generating answers for the set of questions and the candidate question using the content in the document. The method also includes presenting the set of questions, the candidate question, and the answers to a content creator for user verification of accuracy. The method also includes storing a verified set of questions in the document. The verified set of questions includes the candidate question.

Abstract: A system, method and computer program product for conducting questions and answers with deferred type evaluation based on any corpus of data. The method includes processing a query including waiting until a “Type” (i.e. a descriptor) is determined AND a candidate answer is provided. Then, a search is conducted to look (search) for evidence that the candidate answer has the required Lexical Answer Type (e.g., as determined by a matching function that can leverage a parser, a semantic interpreter and/or a simple pattern matcher). Prior to or during candidate answer evaluation, a process is provided for extracting and storing collections of entity-type pairs from semi-structured text documents. During QA processing and candidate answer scoring, a process is implemented to match the query LAT against the lexical type of each provided candidate answer and generate a score judging a degree of match.

Abstract: Mined semantic analysis techniques (MSA) include generating a first subset of concepts, from a NL corpus, that are latently associated with an NL candidate term based on (i) a second subset of concepts from the corpus that are explicitly or implicitly associated with the candidate term and (ii) a set of concept association rules. The concept association rules are mined from a transaction dictionary constructed from the corpus and defining discovered latent associations between corpus concepts. A concept space of the candidate term includes at least portions of both the first and second subset of concepts, and includes indications of relationships between latently-associated concepts and the explicitly/implicitly-associated concepts from which the latently-associated concepts were derived. Measures of relatedness between candidate terms are deterministically determined based on their respective concept spaces.

Abstract: A method for providing adaptation to a question answering (QA) system having an associated plurality of trace data and a question-answer set. The method includes submitting a set of questions to the QA system; receiving back from the QA system a set of answers; comparing the set of answers to answers in the question-answer set; and generating the plurality of trace data based on comparison, and an estimate of how much more training data is needed. The generating comprises (a) for each question type, successively sample an increasing number of question-answer pairs from the question-answer set; (b) automatically train the QA system using the sampled question-answer pairs; (c) automatically compute a functional dependence of the QA system performance on the remaining questions relative to the size of the sample; and (d) extrapolate from the functional dependence a number of training question-answer pairs of each question type.

Abstract: A system, method and computer program product for conducting questions and answers with deferred type evaluation based on any corpus of data. The method includes processing a query including waiting until a “Type” (i.e. a descriptor) is determined AND a candidate answer is provided. Then, a search is conducted to look (search) for evidence that the candidate answer has the required Lexical Answer Type (e.g., as determined by a matching function that can leverage a parser, a semantic interpreter and/or a simple pattern matcher). Prior to or during candidate answer evaluation, a process is provided for extracting and storing collections of entity-type pairs from semi-structured text documents. During QA processing and candidate answer scoring, a process is implemented to match the query LAT against the lexical type of each provided candidate answer and generate a score judging a degree of match.

Abstract: System and method for providing answers to questions based on any corpus of data implements a method that generates a number of candidate passages from the corpus that answer an input query, and finds the correct resulting answer by collecting supporting evidence from the multiple passages. By analyzing all retrieved passages and that passage's metadata in parallel, an output plurality of data structures is generated including candidate answers based upon the analyzing. Then, supporting passage retrieval operations are performed upon the set of candidate answers, and for each candidate answer, the data corpus is traversed to find those passages having candidate answer in addition to query terms. All candidate answers are automatically scored by a plurality of scoring modules, each producing a module score. The modules scores are processed to determine one or more query answers; and, a query response is generated based on the one or more query answers.

Abstract: A computer-implemented system, method and program product generates answers to questions in an input query text string. The method includes determining, by a programmed processor unit, a lexical answer type (LAT) string associated with an input query; automatically obtaining a candidate answer string to the input query from a data corpus; mapping the query LAT string to a first type string in a structured resource; mapping the candidate answer string to a second type string in the structured resource; and determining if the first type string and the second type string are disjointed; and scoring the candidate answer string based on the determination of the types being disjointed wherein the structured resource includes a semantic database providing ontological content.

Abstract: Mined semantic analysis techniques (MSA) include generating a first subset of concepts, from a NL corpus, that are latently associated with an NL candidate term based on (i) a second subset of concepts from the corpus that are explicitly or implicitly associated with the candidate term and (ii) a set of concept association rules. The concept association rules are mined from a transaction dictionary constructed from the corpus and defining discovered latent associations between corpus concepts. A concept space of the candidate term includes at least portions of both the first and second subset of concepts, and includes indications of relationships between latently-associated concepts and the explicitly/implicitly-associated concepts from which the latently-associated concepts were derived. Measures of relatedness between candidate terms are deterministically determined based on their respective concept spaces.

Abstract: A computer-implemented system, method and program product generates answers to questions in an input query text string. The method includes determining, by a programmed processor unit, a lexical answer type (LAT) string associated with an input query; automatically obtaining a candidate answer string to the input query from a data corpus; mapping the query LAT string to a first type string in a structured resource; mapping the candidate answer string to a second type string in the structured resource; and determining if the first type string and the second type string are disjointed; and scoring the candidate answer string based on the determination of the types being disjointed wherein the structured resource includes a semantic database providing ontological content.

Abstract: A model of a domain is received, wherein the model has a plurality of elements. A corpus of select documents covering the plurality of elements of the model is also received. A plurality of select topics is generated from the corpus of select documents. Topics of an additional document are compared to the plurality of select topics to calculate a distance between the topics of the additional document and the plurality of select topics. Upon the distance meeting a threshold value, a new corpus is generated to include the additional document. The new document is annotated with the plurality of elements of the model.

Abstract: According to an aspect, a heterogeneous graph in a data store is accessed. The heterogeneous graph includes a plurality of nodes having a plurality of node types. The nodes are connected by edges having a plurality of relation types. One or more intermediary graphs are created based on the heterogeneous graph. The intermediary graphs include intermediary nodes that are the relation types of the edges of the heterogeneous graph and include intermediary links between the intermediary nodes based on shared instances of the nodes between relation types in the heterogeneous graph. The intermediary graphs are traversed to find sets of relations based on intermediary links according to a template. An inference rule is extracted from the heterogeneous graph based on finding sets of relations in the intermediary graphs. The inference rule defines an inferred relation type between at least two of the nodes of the heterogeneous graph.

Abstract: According to an aspect, a heterogeneous graph in a data store is accessed. The heterogeneous graph includes a plurality of nodes having a plurality of node types. The nodes are connected by edges having a plurality of relation types. One or more intermediary graphs are created based on the heterogeneous graph. The intermediary graphs include intermediary nodes that are the relation types of the edges of the heterogeneous graph and include intermediary links between the intermediary nodes based on shared instances of the nodes between relation types in the heterogeneous graph. The intermediary graphs are traversed to find sets of relations based on intermediary links according to a template. An inference rule is extracted from the heterogeneous graph based on finding sets of relations in the intermediary graphs. The inference rule defines an inferred relation type between at least two of the nodes of the heterogeneous graph.

Abstract: The present disclosure relates generally to question answering systems and methods and, particularly, to systems and methods for domain adaptation in question answering.

Abstract: The present disclosure relates generally to question answering systems and methods and, particularly, to systems and methods for domain adaptation in question answering.

Abstract: The present disclosure relates generally to question answering systems and methods and, particularly, to systems and methods for domain adaptation in question answering.