US 8,131,701 B2 · Method and system for probabilistically quantifying and visualizing relevance between two or more citationally or contextually related data objects

Abstract

In one embodiment the present invention provides a novel method for probabilistically quantifying a degree of relevance between two or more citationally or contextually related data objects, such as patent documents, non-patent documents, web pages, personal and corporate contacts information, product information, consumer to behavior, technical or scientific information, address information, and the like. In another embodiment the present invention provides a novel method for visualizing and displaying relevance between two or more citationally or contextually related data objects. In another embodiment the present invention provides a novel search input/output interface that utilizes an iterative self-organizing mapping (“SOM”) technique to automatically generate a visual map of relevant patents and/or other related documents desired to be explored, searched or analyzed. In another embodiment the present invention provides a novel search input/output interface that displays and/or communicates search input criteria and corresponding search results in a way that facilitates intuitive understanding and visualization of the logical relationships between two or more related concepts being searched.

Claims21

Dependent claims

A computer-implemented method for probabilistically quantifying a likelihood or probability that a direct citational relationship exists between a first document and a second document based on one or more observed indirect citational relationships occurring between said first document and said second document, the method comprising:

determining by a computer system said one or more indirect citational relationships between said first document and said second document;
analyzing by the computer system said one or more indirect citational relationships to determine one or more generational citation counts between said first and second documents at generations higher than said direct first generation citational relationship;
applying by the computer system a probability transform function to said one or more determined generational citation counts to determine or probabilistically quantify a relative event probability that said first document directly cites said second document or said second document directly cites said first document;
calculating by the computer system a probability value based on the relative event probability that said first document directly cites said second document or said second document directly cites said first document,
wherein the applying a probability transform function comprises providing said one or more determined generational citation counts as input predictor variables to a multi-variate regression model, said model being selected and adjusted to determine a relative event probability that said first document directly cites said second document or said second document directly cites said first document based on said one or more determined generational citation counts,
wherein the computer system comprises at least a processor and a storage device.

3 more elements

A computer-implemented method for rating or ranking the relative quality or value of a first patent document based at least in part on determining a relative probability that a direct citational relationship exists between said first patent document and a second patent document, the method comprising:

determining by a computer system one or more indirect citational relationships that may exist between said first patent document and said second patent document;
analyzing by the computer system said one or more indirect citational relationships by determining for each said indirect citational relationship the number of citation links or generations separating said first patent document from said second patent document and counting or aggregating said indirect citational relationships into generational citation counts according to said determined number of citation links or generations;
applying by the computer system a probability transform function to said one or more determined generational citation counts to determine or quantify the relative probability that said first patent document directly cites said second patent document or said second patent document directly cites said first patent document;
wherein the applying a probability transform function comprises providing said one or more determined generational citation counts as input predictor variables to a multi-variable event prediction model, said model being selected and adjusted to determine a relative event probability that said first document directly cites said second document or said second document directly cites said first document based on said one or more determined generational citation counts;
and
providing by the computer system said determined relative probability to a computer-implemented patent rating system and causing said computer-implemented patent rating system to thereby rate or rank the relative quality or value of said first patent document based at least in part on said determined relative probability,
wherein the computer system comprises at least a processor and a storage device.

4 more elements

Dependencies are inferred from the claim text.

Method and system for probabilistically quantifying and visualizing relevance between two or more citationally or contextually related data objects

Life of this patent

Method and system for probabilistically quantifying and visualizing relevance between two or more citationally or contextually related data objects

Life of this patent

Abstract

Claims21