METHOD AND SYSTEM FOR PROBABILISTICALLY QUANTIFYING AND VISUALIZING RELEVANCE BETWEEN TWO OR MORE CITATIONALLY OR CONTEXTUALLY RELATED DATA OBJECTS

• US 20120221580A1
• Filed: 03/02/2012
• Published: 08/30/2012
• Est. Priority Date: 09/27/2005
• Status: Active Grant

• Current Assignee: PatentRatings, LLC
• Original Assignee: PatentRatings, LLC
• Inventors: Barney, Jonathan A.
• Granted Patent: US 8,504,560 B2
• Time in Patent Office: Days
• US Class Current: 707/748
• CPC Class Codes: G06F 16/14 Details of searching files based on file metadata
• CPC Class Codes: G06F 16/2228 Indexing structures
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/2465 Query processing support for facilitating data mining operations in structured databases
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/26 Visual data mining; Browsing structured data
• CPC Class Codes: G06F 16/334 Query execution G06F16/335 takes precedence
• CPC Class Codes: G06F 16/3346 using probabilistic model
• CPC Class Codes: G06F 16/34 Browsing; Visualisation therefor
• CPC Class Codes: G06F 16/382 using citations hypermedia G06F16/94
• CPC Class Codes: G06F 16/93 Document management systems
• CPC Class Codes: G06F 16/95 Retrieval from the web
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 2216/11 Patent retrieval
• CPC Class Codes: Y10S 707/912 Applications of a database
• CPC Class Codes: Y10S 707/923 Intellectual property
• CPC Class Codes: Y10S 707/93 intellectual property analysis
• CPC Class Codes: Y10S 707/933 Citation analysis
• CPC Class Codes: Y10S 707/937 intellectual property searching

Abstract

In one embodiment a 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 is provided. In another embodiment a method for visualizing and displaying relevance between two or more citationally or contextually related data objects is provided. In another embodiment a search input/output interface that utilizes an iterative self-organizing mapping technique to automatically generate a visual map of relevant patents and/or other related documents desired to be explored, searched or analyzed is provided. In another embodiment, a 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 is provided.

Claims

1. A computer-implemented method, comprising:

receiving a first set of information identifying an input set of documents, said input set comprising a plurality of documents;

identifying an additional document that is not a member of the input set, but which is citationally related to at least some of the documents in the input set;

programmatically calculating a data value that represents a degree to which said document is citationally related to the at least some of the documents in the input set, said data value dependent upon at least (a) how many citational relationships exist at generations higher than a first generation between the input set of documents and said additional document, and (b) generation levels of said citational relationships, wherein calculating said data value comprises assigning different amounts of weight to citational relationships of different generation levels, said amounts of weight being based on an analysis in which multi-generation citational relationships between documents are used to predict existences of first generation citational relationships between documents, said analysis performed over a document population; and

storing the data value in computer storage in association with identifiers of the first and second documents.