초록 ▼

Information retrieval systems face challenging problems with delivering highly relevant and highly inclusive search results in response to a user's query. Contextual personalized information retrieval uses a set of integrated methodologies that can combine automatic concept extraction/matching from

Information retrieval systems face challenging problems with delivering highly relevant and highly inclusive search results in response to a user's query. Contextual personalized information retrieval uses a set of integrated methodologies that can combine automatic concept extraction/matching from text, a powerful fuzzy search engine, and a collaborative user preference learning engine to provide accurate and personalized search results. The system can include constructing a search query to execute a search of a database. The system can parse an input query from a user conducting the search of the database into sub-strings, and can match the sub-strings to concepts in a semantic concept network of a knowledge base. The system can further map the matched concepts to criteria and criteria values that specify a set of constraints on and scoring parameters for the matched concepts.

대표청구항 ▼

I claim: 1. A method for using indexes to search a knowledge base in at least one computer system, the method executed by the computer system and comprising:accessing a knowledge base comprising a semantic network of relationships among concepts, each concept having a set of values associated with i

I claim: 1. A method for using indexes to search a knowledge base in at least one computer system, the method executed by the computer system and comprising:accessing a knowledge base comprising a semantic network of relationships among concepts, each concept having a set of values associated with it, wherein each concept is an instance of a category and each value is an instance of an attribute and wherein categories and attributes form a knowledge base schema;receiving, from a user searching for one or more target concepts, a query represented as criteria and criteria values that specify constraints on the categories and the attributes;executing a search of the concepts and the values of the knowledge base to retrieve the one or more target concepts using indexes selected from a group consisting of: a) one or more transitive indexes that index transitive relationships from concepts in a first category through at least one second category to concepts in a third category and b) one or more transitive closure indexes that index transitive closure relationships amongst concepts within a category; andretrieving a result subset of the target concepts and the values that satisfies the criteria and criteria values.