Visualization of information using graphical representations of context vector based relationships and attributes
AssigneeHNC Software, Inc.
InventorsWilliam Robert Caid, Joel Lawrence Carleton
Life of this patent
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AssigneeHNC Software, Inc.
InventorsWilliam Robert Caid, Joel Lawrence Carleton
Estimating the term…
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.
A computer-implemented process of providing a visual representation of information content for a record in a computer system including a display device for displaying visual information at positions on a display screen, the record having a stored summary vector, the process comprising:
A computer-implemented process of providing a visual representation of information content for a record in a computer system including a display device for displaying the visual representation, the display device and visual representation having modifiable visual attributes that modify the display of the visual representation, the record having a stored summary vector, the process comprising:
A computer-implemented process of providing a visual representation of information content for a record in a computer system including a display device for displaying the visual representation, the display device and visual representation having modifiable visual attributes that modify the display of the visual representation, the record having a stored summary vector having a plurality of components, the process comprising:
A computer readable media storing thereon a program product executable by a processor for providing a visual representation of information content for a record in a computer system including a display device for displaying visual representations at positions on a display screen, the display device and visual representations having modifiable visual attributes that modify the display of the visual representations, the record stored in a memory and having a summary vector having a plurality of components, the program product comprising:
A computer readable media storing thereon a program product executable by a processor for providing a visual representation of information content for a record, the record stored in memory and having a summary vector having a plurality of components, the program product comprising:
In a computer with a processor and memory, a computer-implemented method of determining a similarity between a first data item and a second data item in a corpus of data items stored in the memory, the method comprising:
In a computer comprising a processor, a computer-implemented method for associating a first data domain comprising a plurality of first information elements with a second data domain comprising a plurality of second information elements to form a universal meaning space to provide a meaning for second information elements from a known meaning of first information elements, the first information elements having measurable proximity between any pair of first information elements, each first information element having a frequency of occurrence in the first data domain, the second information elements having a measurable proximity between any pair of second information elements, each second information element having a frequency of occurrence in the second data domain, the method comprising the steps of:
Dependencies are inferred from the claim text.