Abstract: In one embodiment, a method for determining query return referent data for concept types in a conceptual graph includes generating a conceptual graph for a document query, the conceptual graph comprising a plurality of graph terms, identifying one of more of the plurality of graph terms needing referent data, identifying conceptually similar terms for each of the graph terms, for the graph terms needing referents, identifying referent data by searching for instances where conceptually similar terms for graph terms needing referent data are associated by conceptually similar terms for the linking concept term, and associating identified referent data with the graph terms needing referent data.

Abstract: According to one embodiment, categorizing concept types of a conceptual graph includes receiving the conceptual graph comprising one or more concept types, one or more relationship types, and one or more arcs. Each concept type is categorized according to the relationship types and the arcs. The categorization of the each concept type is recorded.

Abstract: A system for ontology candidate selection and comparison including a microprocessor and an ontology candidate selection component executing on the microprocessor and configured to compare at least a portion of a plurality of ontology candidates based on a candidate selection rule, and based on said comparison, select from the plurality of ontology candidates a pair of ontologies. The system further includes an ontology similarity component coupled to the ontology candidate selection component and configured to generate a similarity outcome related to the pair of ontologies based on a similarity rule and evaluate at least one of: the candidate selection rule or the similarity rule based on the similarity outcome.

Abstract: In one embodiment, a method for determining concept attributes for a concept term includes receiving a concept term and determining one or more word senses for the concept term. A word sense is selected from the one or more word senses, and, based on the selected word sense, one or more conceptually similar terms for the concept term is determined. The method also includes determining that at least one of the one or more conceptually similar terms is a concept attribute for the concept term and generating a mapping to associate the concept attribute with the concept term. The mapping is stored in an onomasticon.

Abstract: In one embodiment, searching documents includes generating a query conceptual graph for a search query. The query conceptual graph has graph terms representing concept types. A set of conceptually similar terms is identified for each graph term, and the set is mapped to the concept type represented by the graph term. Documents are searched in accordance with the set of conceptually similar terms. In another embodiment, selecting a document includes determining documents that satisfy a search query expressed as a query conceptual graph. A document conceptual graph that has graph terms representing concept types is generated for each document. A set of conceptually similar terms is identified for each graph term, where the set is mapped to the concept type represented by the graph term. A document is selected if terms of the sets associated with the document match terms associated with the query conceptual graph.

Abstract: A method for multilingual data querying comprises sending one or more words in an original language to a word ontology. The method further comprises receiving sense descriptions of the one or more words from the word ontology, and selecting one or more sense descriptions of the one or more words and a language for querying. The method further comprises translating the one or more sense descriptions into the language for querying, and also translating the one or more sense descriptions back into the original language for verification. The method further comprises selecting at least one of the one or more sense descriptions to use in a query.

Abstract: A system for ontology candidate selection and comparison including a microprocessor and an ontology candidate selection component executing on the microprocessor and configured to compare at least a portion of a plurality of ontology candidates based on a candidate selection rule, and based on said comparison, select from the plurality of ontology candidates a pair of ontologies. The system further includes an ontology similarity component coupled to the ontology candidate selection component and configured to generate a similarity outcome related to the pair of ontologies based on a similarity rule and evaluate at least one of: the candidate selection rule or the similarity rule based on the similarity outcome.

Abstract: According to one embodiment, attributes associated with a concept type of a query conceptual graph are received. A potentially conceptually similar term is received from an onomasticon. The potentially conceptually similar term is validated according to the attributes. According to another embodiment, attributes associated with a concept type of a document conceptual graph are received. A potentially conceptually similar term is received from an onomasticon. The potentially conceptually similar term is validated according to the attributes.

Abstract: Disclosed is a system and method for expanding variables within a computational model. The computational model, which can be a Bayesian-network, includes input and output variables that are interrelated via a conditional probability table. Term expansion is accomplished via a lexical database and a logic engine to determine semantic equivalents that are relevant to the computational model. The expanded terms allow the computational model to be related to instance data, which may be in the form of a dynamic ontology. Input variable expansion permits the computational model to be populated with semantically relevant instance data from the ontology, and output variable expansion permits the computational model to be associated with semantically relevant ontology nodes.

Abstract: Disclosed is a system and method for determining the probability of an event occurring. The method involves developing models relating a number of factors and variables. The factors and variables can be unique to a specified field of endeavor, such as military security or epidemiology. The models can be ontological models. A rule set is then utilized to relate certain variables in the models to a specific event. The rule set can be embodied in a computer model, such as a Bayesian-Network. The system permits a user to query a knowledge store or database to acquire referent values for the rule set. Thereafter, the referent values are used to populate the rule set and compute the probability of the event occurring.

Abstract: In one aspect, a method for multilingual data querying, includes determining a word ontology of a base word in a source language, generating a set of words representing the word ontology of the base word, translating at least a subset of the set of words into a target language and translating the at least a subset of the set of words from the target language into the source language of the base word.

Abstract: According to one embodiment, searching media includes receiving a search query comprising search terms. At least one search term is expanded to yield a set of conceptually equivalent terms. The set of conceptually equivalent terms is converted to a set of search phonemes. Files that record phonemes are searched according to the set of search phonemes. A file that includes a phoneme that matches at least one search phoneme is selected and output to a client.

Abstract: In one aspect, a method for multilingual data querying includes receiving a request for a query. The query includes a base word in a source language used for a search of a database in a target language. The method further includes applying the request to factors, selecting components based on the factors and performing the query based on the selecting.

Abstract: In one embodiment, searching documents includes generating a query conceptual graph for a search query. The query conceptual graph has graph terms representing concept types. A set of conceptually similar terms is identified for each graph term, and the set is mapped to the concept type represented by the graph term. Documents are searched in accordance with the set of conceptually similar terms. In another embodiment, selecting a document includes determining documents that satisfy a search query expressed as a query conceptual graph. A document conceptual graph that has graph terms representing concept types is generated for each document. A set of conceptually similar terms is identified for each graph term, where the set is mapped to the concept type represented by the graph term. A document is selected if terms of the sets associated with the document match terms associated with the query conceptual graph.

Abstract: According to one embodiment, categorizing concept types of a conceptual graph includes receiving the conceptual graph comprising one or more concept types, one or more relationship types, and one or more arcs. Each concept type is categorized according to the relationship types and the arcs. The categorization of the each concept type is recorded.

Abstract: In one embodiment, a method for expanding concept attributes for a concept term includes receiving an attribute term for expansion and determining one or more word senses for the attribute term. A word sense is selected from the one or more word senses. One or more conceptually similar terms is selected for the attribute term based on the word sense and it is determined that that at least one of the one or more conceptually similar terms is an additional attribute. A first mapping associating the additional attribute with the attribute term is generated, and a second mapping associating the additional attribute with the concept term is generated. The mappings are stored in an onomasticon.

Abstract: In one embodiment, a method for determining concept attributes for a concept term includes receiving a concept term and determining one or more word senses for the concept term. A word sense is selected from the one or more word senses, and, based on the selected word sense, one or more conceptually similar terms for the concept term is determined. The method also includes determining that at least one of the one or more conceptually similar terms is a concept attribute for the concept term and generating a mapping to associate the concept attribute with the concept term. The mapping is stored in an onomasticon.

Abstract: In one embodiment, a method for determining referents for concept types in a conceptual graph includes generating a conceptual graph for a search query, the conceptual graph comprising a plurality of graph terms, identifying at least one graph term needing referents, identifying referents for each graph term needing referents by searching for instances where conceptually similar terms for graph terms needing referents are associated by conceptually similar terms for the linking concept term; and associating identified referents with the graph terms needing referents.

Abstract: In one embodiment, a method for determining query return referent data for concept types in a conceptual graph includes generating a conceptual graph for a document query, the conceptual graph comprising a plurality of graph terms, identifying one of more of the plurality of graph terms needing referent data, identifying conceptually similar terms for each of the graph terms, for the graph terms needing referents, identifying referent data by searching for instances where conceptually similar terms for graph terms needing referent data are associated by conceptually similar terms for the linking concept term, and associating identified referent data with the graph terms needing referent data.

Abstract: According to one embodiment, attributes associated with a concept type of a query conceptual graph are received. A potentially conceptually similar term is received from an onomasticon. The potentially conceptually similar term is validated according to the attributes. According to another embodiment, attributes associated with a concept type of a document conceptual graph are received. A potentially conceptually similar term is received from an onomasticon. The potentially conceptually similar term is validated according to the attributes.