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Method and system for guided cluster based processing on prototypes

Patent 7308451 Issued on December 11, 2007. Estimated Expiration Date: Icon_subject December 14, 2021. Estimated Expiration Date is calculated based on simple USPTO term provisions. It does not account for terminal disclaimers, term adjustments, failure to pay maintenance fees, or other factors which might affect the term of a patent.

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Inventors

Assignee

Application

No. 10017504 filed on 12/14/2001

US Classes:

707/100, DATABASE SCHEMA OR DATA STRUCTURE707/3, Query processing (i.e., searching)707/5Query augmenting and refining (e.g., inexact access)

Examiners

Primary: Mofit, Apu
Assistant: Nguyen, Cindy

Attorney, Agent or Firm

International Classes

G06F 17/00
G06F 7/00

Abstract

A method (and system) for clustering a plurality of items. Each of the items includes information. The method includes inputting a plurality of items. Each of the items includes information. The items are provided into a clustering process. The method also inputs an initial organization structure into the clustering process. The initial organization structure includes one or more categories, at least one of the categories being associated with one of the items. The method processes the plurality of items based upon at least the initial organization structure and the information in each of the items; and determines a resulting organization structure based upon the processing. The resulting organization structure relates to the initial organization structure.

Other References

  • Jane and Dubes, “Algorithms for Clustering Data”, Prentice Hall, (1988) QA 278, J341, Chapter 3, pp. 55-142.
  • Willett, “Document Clustering Using an Inverted File Approach”, Journal of Information Science 2 (1980) pp. 223-231.
  • Iwayama et al., “Hierarchical Bayesian Clustering for Automatic Text Classification”, Proceedings of the Fourteenth Intl. Joint Conference on Artificial Intelligence, vol. 2, (Aug. 1995) pp. 1322-1327.
  • Fraley, “Algorithms For Model-Based Gaussian Hierarchical Clustering”, SIAM J. Sci. Comput., vol. 20, No. 1, (1998) pp. 270-281.
  • Fraley et al., “How Many Cluster? Which Clustering Method? Answers Via Model-Based Cluster Analysis”, The Computer Journal, vol. 41, No. 8, (1998) pp. 578-588.
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