Computer-implemented patent portfolio analysis method and apparatus

• US 20040181427A1
• Filed: 03/22/2004
• Published: 09/16/2004
• Est. Priority Date: 02/05/1999
• Status: Active Grant

• Current Assignee: Ontologics Incorporated
• Original Assignee: Gregory A. Stobbs, John V. Biernacki
• Inventors: Biernacki, John V., Stobbs, Gregory A.
• Granted Patent: US 8,095,581 B2
• Time in Patent Office: Days
• US Class Current: 705/1
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis
• CPC Class Codes: G06Q 50/184 Intellectual property management
• CPC Class Codes: Y10S 707/934 Analyzing patent activity

Abstract

A computer-implemented apparatus and method for performing patent portfolio analysis. The patent portfolio analysis apparatus and method clusters a group of patents based upon one or more techniques. The clustering techniques include linguistic clustering techniques (e.g., eigenvector analysis), claim meaning, and patent classification techniques. Different aspects of the clusters are analyzed, including financial, claim breadth, and assignee patent comparisons. Moreover, patents and/or their clusters are linked to the Internet in order to determine what products might be covered by the claims of the patents or whether materials on the Internet might render patent claims invalid.

Claims

1. A computer-implemented patent portfolio analysis method comprising:

retrieving a corpus of patent information from a database, said information including the claim text of at least one claim;

analyzing the claim text of said at least one claim to generate a claim breadth metric;

associating said claim breadth metric with said claim text and storing said associated metric in a computer-readable dataset.

2. The method of claim 1 wherein said step of analyzing the claim text includes counting the number of words in said claim text and generating a claim breadth metric therefrom.

3. The method of claim 1 wherein said step of analyzing the claim text includes identifying within said claim text a preamble portion and a body portion, counting the number of words in said preamble and body portions and applying separate weights to said counts to generate said claim breadth metric.

4. The method of claim 1 wherein said step of analyzing the claim text includes parsing said text to identify parts of speech, using said identified parts of speech to identify clauses within said claim, comparing said clauses with the text of other claims in said corpus to generate scores indicative of which clauses within said claim text have a lower probability of being found in other claims within said corpus.

5. The method of claim 1 further comprising displaying said patent information in a sorted order based on said claim breadth metric.

6. The method of claim 1 wherein said step of analyzing the claim text includes linguistically processing said text to identify at least one clause within said claim text that has a lower probability than other of said clauses within said claim text of being found in other claims within said corpus.

7. The method of claim 6 further comprising displaying said claim text such that said one clause is visually presented differently than the other of said clauses.

8. A computer-implemented patent portfolio analysis method comprising:

retrieving a corpus of patent information from a database;

analyzing said patent information to generate a category metric; and

associating said category metric with said patent information and storing said associated metric in a computer-readable dataset.

9. The method of claim 8 wherein said patent information includes patent classification information and wherein said analyzing step is performed by defining a plurality of categories and mapping classification information onto said categories.

10. The method of claim 8 wherein said patent information includes claim text information to be analyzed and wherein said analyzing step includes:

defining an eigenspace representing a training population of training claims each training claim having associated training text;

representing at least a portion of said training claims in said eigenspace and associating a predefined category with each training claim in said eigenspace; and

projecting the claim text information to be analyzed into said eigenspace and associating with said projected claim text the predefined category of the training claim to which it is closest within the eigenspace.