05794178 is referenced by 394 patents and cites 7 patents.

A system and method for generating context vectors for use in storage and retrieval of documents and other information items. Context vectors represent conceptual relationships among information items by quantitative means. A neural network operates on a training corpus of records to develop relationship-based context vectors based on word proximity and co-importance using a technique of "windowed co-occurrence". Relationships among context vectors are deterministic, so that a context vector set has one logical solution, although it may have a plurality of physical solutions. No human knowledge, thesaurus, synonym list, knowledge base, or conceptual hierarchy, is required. Summary vectors of records may be clustered to reduce searching time, by forming a tree of clustered nodes. Once the context vectors are determined, records may be retrieved using a query interface that allows a user to specify content terms, Boolean terms, and/or document feedback. The present invention further facilitates visualization of textual information by translating context vectors into visual and graphical representations. Thus, a user can explore visual representations of meaning, and can apply human visual pattern recognition skills to document searches.

Title
Visualization of information using graphical representations of context vector based relationships and attributes
Application Number
124098
Publication Number
5794178
Application Date
April 12, 1996
Publication Date
August 11, 1998
Inventor
Joel Lawrence Carleton
San Diego
CA, US
William Robert Caid
San Diego
CA, US
Agent
Fenwick & West
Assignee
HNC Software
CA, US
IPC
G06F 17/16
G06F 17/30
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