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Title: US7233943: Clustering hypertext with applications to WEB searching
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Country: US United States of America

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19 pages

 
Inventor: Modha, Dharmendra Shantilal; San Jose, CA, United States of America
Spangler, William Scott; San Martin, CA, United States of America

Assignee: International Business Machines Corporation, Armonk, NY, United States of America
other patents from INTERNATIONAL BUSINESS MACHINES CORPORATION (280070) (approx. 44,393)
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Published / Filed: 2007-06-19 / 2003-09-11

Application Number: US2003000660242

IPC Code: Advanced: G06F 7/00; G06F 17/30;
Core: more...

ECLA Code: G06F17/30W1;

U.S. Class: Current: 707/003; 707/010; 707/E17.108; 715/234;
Original: 707/003; 707/010; 715/513;

Field of Search: 707/002,3,5,6,10,104.1,4 715/513,501.1,532

Priority Number:
2003-09-11  US2003000660242
2000-10-18  US2000000690854

Abstract:     A method of searching a database of documents, wherein the method includes performing a search of the database using a query to produce query result documents; constructing a word dictionary of words within the query result documents; constructing an out-link dictionary of documents within the database that are pointed to by the query result documents; adding the query result documents to the out-link dictionary; constructing an in-link dictionary of documents within the database that point to the query result documents; and adding the query result documents to the in-link dictionary.

Attorney, Agent or Firm: Gibb I.P. Law Firm, LLC ; McSwain, Esq., Marc ;

Primary / Asst. Examiners: Gaffin, Jeffrey; Veillard, Jacques

INPADOC Legal Status: None          Buy Now: Family Legal Status Report

       
Related Applications:
Application Number Filed Patent Pub. Date  Title
US2000000690854 2000-10-18    2004-01-27  Clustering hypertext with applications to web searching


       
Parent Case: CROSS-REFERENCE TO RELATED APPLICATIONS
    This application is a division of U.S. application Ser. No. 09/690,854 filed Oct. 18, 2000, now U.S. Pat. No. 6,684,205 the complete disclosure of which, in its entirety, is herein incorporated by reference.

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First Claim:
Show all 20 claims
    1. A method of searching a database of documents, said method comprising:

performing a search of said database using a query to produce query result documents;

constructing a word dictionary of words within said query result documents;

constructing an out-link dictionary of documents within said database that are pointed to by said query result documents;

adding said query result documents to said out-link dictionary;

constructing an in-link dictionary of documents within said database that point to said query result documents; and

adding said query result documents to said in-link dictionary.



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U.S. References: Go to Result Set: All U.S. references   |  No patents reference this one   |   Backward references (20)   |   Citation Link

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Patent  Pub.Date  Inventor Assignee   Title
Buy PDF- 11pp US5787420  1998-07 Tukey et al.  Xerox Corporation Method of ordering document clusters without requiring knowledge of user interests
Buy PDF- 11pp US5787421  1998-07 Nomiyama  International Business Machines Corporation System and method for information retrieval by using keywords associated with a given set of data elements and the frequency of each keyword as determined by the number of data elements attached to each keyword
Buy PDF- 15pp US5819258  1998-10 Vaithyanathan et al.  Digital Equipment Corporation Method and apparatus for automatically generating hierarchical categories from large document collections
Buy PDF- 19pp US5835905  1998-11 Pirolli et al.  Xerox Corporation System for predicting documents relevant to focus documents by spreading activation through network representations of a linked collection of documents
Buy PDF- 18pp US5857179  1999-01 Vaithyanathan et al.  Digital Equipment Corporation Computer method and apparatus for clustering documents and automatic generation of cluster keywords
Buy PDF- 8pp US5864845  1999-01 Voorhees et al.  Siemens Corporate Research, Inc. Facilitating world wide web searches utilizing a multiple search engine query clustering fusion strategy
Buy PDF- 19pp US5895470  1999-04 Pirolli et al.  Xerox Corporation System for categorizing documents in a linked collection of documents
Buy PDF- 14pp US5920859  1999-07 Li  IDD Enterprises, L.P. Hypertext document retrieval system and method
Buy PDF- 28pp US6012058  2000-01 Fayyad et al.  Microsoft Corporation Scalable system for K-means clustering of large databases
Buy PDF- 14pp US6038574  2000-03 Pitkow et al.  Xerox Corporation Method and apparatus for clustering a collection of linked documents using co-citation analysis
Buy PDF- 14pp US6115708  2000-09 Fayyad et al.  Microsoft Corporation Method for refining the initial conditions for clustering with applications to small and large database clustering
Buy PDF- 18pp US6122647  2000-09 Horowitz et al.  Perspecta, Inc. Dynamic generation of contextual links in hypertext documents
Buy PDF- 16pp US6256648  2001-07 Hill et al.  AT&T Corp. System and method for selecting and displaying hyperlinked information resources
Buy PDF- 10pp US6298174  2001-10 Lantrip et al.  Battelle Memorial Institute Three-dimensional display of document set
Buy PDF- 7pp US6363379  2002-03 Jacobson et al.  AT&T Corp. Method of clustering electronic documents in response to a search query
Buy PDF- 32pp US6389436  2002-05 Chakrabarti et al.  International Business Machines Corporation Enhanced hypertext categorization using hyperlinks
Buy PDF- 57pp US6460036  2002-10 Herz  Pinpoint Incorporated System and method for providing customized electronic newspapers and target advertisements
Buy PDF- 90pp US6556983  2003-04 Altschuler et al.  Microsoft Corporation Methods and apparatus for finding semantic information, such as usage logs, similar to a query using a pattern lattice data space
Buy PDF- 19pp US6684205  2004-01 Modha et al.  International Business Machines Corporation Clustering hypertext with applications to web searching
Buy PDF- 11pp US6862586  2005-03 Kreulen et al.  International Business Machines Corporation Searching databases that identifying group documents forming high-dimensional torus geometric k-means clustering, ranking, summarizing based on vector triplets
       
Foreign References: None

Other References:
  • Kuo et al., Web Document Classification based on Hyperlinks and Document Semantics, Aug. 2000, PRICAI 2000 Workshop on Text and Web Mining, pp. 44-51.
  • Pirolli et al., Silk from a Sow's Ear: Extracting Usable Structures from the Web, 1996, CHI, pp. 1-9.
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  • Modha et al., Clustering Hypertext with Applications to Web Searching, 2000, ACM, pp. 143-152.
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  • Silverstein et al., “Analysis of a Very Large Alta Vista Query Log”, SRC Technical Note 26, 1998, pp. 1-17.
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  • Kleinberg, Jon M., “Authoritative Sources in a Hyperlinked Environment”, Proceedings of the ACM-SIAM Symposium on Discrete Algorithms, 1998, IBM Research Report RJ 10076, May 1997, pp. 1-33.
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  • Chakrabarti, S., Dom, B., Raghavan, P., Rajagopalan, S., Gibson, D., Kleinberg, J., “Automatic Resource Compilation by Analyzing Hyperlink Structure and Associated Text”, WWW7, 1998, pp. 1-14.
  • Bradley, P.S. and Fayyad, Usama M., “Refining Initial Points for K-Means Clustering”, ICML, 1998, pp. 91-99.
  • Chakrabarti, S., Dom, B.E., Kumar, S.R., Raghayan, P., Rajagopalan, S., Tomkins, A., Kleinberg, J.M., and Gibson, D., “Hypersearching the Web”, Scientific American, Jun. 1999, pp. 1-8.
  • Weiss, R., Velez, B., Sheldon, M.A., Namprempre, C., Szilagyi, P., Duda, A., Gifford, D.K., “Hypursuit: A Hierarchical Network Search Engine that Exploits Content-Link Hypertext Clustering”, ACM Hypertext, 1996, pp. 180-193.
  • Mukherjea, S., Foley, J.D., Hudson, S.E., “Interactive Clustering for Navigating in Hypermedia Systems”, ACM Hypertext, Sep. 1994, pp. 136-145.
  • Chen, C., “Structuring and Visualising the Web by Generalised Similarity Analysis”, ACM Hypertext, 1997.
  • Pirolli, P., Pitkow, J., Rao, R., “Silk from A Sow's Ear: Extracting Usable Structures from the Web” ACM, SIGCHI Human Factors Comput., 1996.
  • Chen, C., Czerwinski, M., “From Latent Semantics to Spatial Hypertex—An Integrated Approach”, ACM Hypertext, 1998, pp. 77-86.
  • Botafogo, R.A., “Cluster Analysis for Hypertext Systems”, ACM-SIGIR Jun. 1993, pp. 116-125.
  • Rasmussent, E., “Clustering Algorithms”, Information Regrieval: Data Structures and Processes, 1992, pp. 419-442.
  • Hartigan, “Clusterin Algorithms,” Wiley Publication, Chapter 4, 1975, pp. 84-107.
  • P. Willet, “Recent Trends in Hierarchic Document Clustering”, Inform. Proc. & Management, 1988, pp. 577-597.
  • Frakes et al., “Information Retrieva:l Data Structures & Algorithms”, Clustering Algorithms, Chapter 16, 419-442, 1992.
  • Chen et al., “From LatexSemantics to Spatial Hypertext An Integrated Approach”, In Proceedings of Hypertext, 1998, pp. 77-86.
  • Weiss et al., “Hy Pursuit: A Hierarchial Network Search Engine that Exploits Content-Link Hypertext Clustering,” In Proc. of Hypertext, 1996, pp. 180-193.


  • Continuity Data:
    Application Number Filed Notes

    US2003000660242 2003-09-11  is a related to the prior publication
         US20040049503A1 issued 2004-03-11  Clustering hypertext with applications to WEB searching

    >US2003000660242< 2003-09-11  is a division of
    US2000000690854  2000-10-18   (pending) [presumed granted]
         US6684205 issued 2004-01-27   Clustering hypertext with applications to web searching

    >US2003000660242<   is a division of
    US2000000690854  2000-10-18
         US6684205 issued 2004-01-27   Clustering hypertext with applications to web searching


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