Method and system for identifying relationships between text...

Data processing: presentation processing of document – operator i – Presentation processing of document – Edit – composition – or storage control

Reexamination Certificate

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C707S765000

Reexamination Certificate

active

07810029

ABSTRACT:
A method and system for interesting relationships in text documents includes generating a dictionary of keywords in the text documents, forming categories of the text documents using the dictionary and an automated algorithm, counting occurrences of the structured variables, categories and structured variable/category combinations in the text documents, and calculating probabilities of occurrences of the structured variable/category combinations.

REFERENCES:
patent: 5122951 (1992-06-01), Kamiya
patent: 5251268 (1993-10-01), Colley
patent: 5371673 (1994-12-01), Fan
patent: 5384703 (1995-01-01), Withgott et al.
patent: 5414797 (1995-05-01), Vassiliadis
patent: 5544360 (1996-08-01), Lewak et al.
patent: 5659766 (1997-08-01), Saund
patent: 5675710 (1997-10-01), Lewis
patent: 5694592 (1997-12-01), Driscoll
patent: 5819258 (1998-10-01), Vaithyanathan
patent: 5857179 (1999-01-01), Vaithyanathan et al.
patent: 5963965 (1999-10-01), Vogel
patent: 6038574 (2000-03-01), Pitkow
patent: 6047277 (2000-04-01), Parry
patent: 6100901 (2000-08-01), Mohda et al.
patent: 6233575 (2001-05-01), Agrawal
patent: 6236768 (2001-05-01), Rhodes
patent: 6301577 (2001-10-01), Matsumoto
patent: 6374251 (2002-04-01), Fayyad
patent: 6424971 (2002-07-01), Kreulen
patent: 6556958 (2003-04-01), Chickering
patent: 6584456 (2003-06-01), Dom
patent: 6609124 (2003-08-01), Chow
patent: 6611825 (2003-08-01), Billheimer
patent: 6618725 (2003-09-01), Fukuda
patent: 6654739 (2003-11-01), Apte
patent: 6701305 (2004-03-01), Holt
patent: 6718367 (2004-04-01), Ayyadurai
patent: 6751621 (2004-06-01), Calistri-Yeh
patent: 6778995 (2004-08-01), Gallivan
patent: 6804688 (2004-10-01), Kobayashi et al.
patent: 2002/0156810 (2002-10-01), Holland et al.
patent: 2003/0033274 (2003-02-01), Chow et al.
patent: 2003/0167163 (2003-09-01), Glover et al.
patent: 2004/0093331 (2004-05-01), Garner et al.
patent: 2004/0243561 (2004-12-01), Cody et al.
patent: 2005/0022115 (2005-01-01), Baumgartner et al.
Goldman et al., “Knowledge Discovery in an Earthquake Text Database: Correlation Between Significant Earthquakes and the Time of Day”, IEEE pp. 12-21, 1997.
Goldszmidt et al., “A Probabilistic Approach to Full-Text Document Clustering”, Technical Report ITAD-433-MS-98-044, SRI International, 1998.
Goldman Time et al.,“Knowledge Discovery in an Earthquake Text Database: Correlation between Significant Earthquakes and the Time of Day”, In “Statistical and Scientific Database ManManagement”, pp. 12-21,1997.
Singh et al.,“Rethinking the Presentation of Results From Web Search”, In: Multimedia and Expo, 2005. ICME 2005. IEEE, Jun. 6-Jul. 2005, pp. 1492 -1495.
Chien et al.,“Semantic Similarity Between Search Engine Queries”, WWW 2005, May 10-14, 2005 pp. 2-11.
Shyu et al.,“Affinity-Based Similarity Measure for Web Document Clustering”, Univ. of Miami, date unknown.
Author unknown,“Details of Clustering Algorithms”, downloaded from http://maya.cs.depaul.edu/˜classes/ds575/clustering/CL-alg-details.html, Jun. 27, 2005.
Rasmussen et al., “wCLUTO: A Web-Enabled Clustering Toolkit”, Univ. of Minnesota, date unknown.
Zhao et al, “Evaluation of Hierarchical Clustering Algorithms for Document Datasets”, ACM, 2002.
Pons-Porrata et al., “Detecting events and topics by using temporal references”, 2002.
J. Allan et al, “Topic Detection and Tracking Pilot Study Final Report”, Feb. 1998, Proc. of the DARPA Broadcast News Transcription and Understanding Workshop.
M. Goldszmidt et al., “A Probabilistic Approach to Full-Text Document Clustering”, 1998, SRI International.
M. Sahami, “Using Machine Learning to Improve Information Access”, copyright date unknown, CompSci, Stanford Univ, used for background information only.
I. Dhillon et al., “Efficient Clustering of Very Large Document Collections”, in Data Mining for Scientific and Engineering Applications“,Kluwer Academic Publishers”, 2001 used for background information only.
A. Popescul et al, “Clustering and Identifying Temporal Trends in Document Databases”, 2000, In Proc. IEEE Advances in Digital Libraries, used for background information only.
Y. Yang et al., “Learning Approaches for Detecting and Tracking NEws Events”, 1999, IEEE Intelligent Systems.
Y. Yang et al., “A Study of Retrospective and On-Line Event Detection”, SIGR 1998 Mebourne Australia, used for background information only.
J. Allan et al., “On-Line New Event Detection and Tracking”, 1998, SIGR'98 Mebourne Australia, ACM used for background information only.
J. Makkonen et al., “Utilizing Temporal Information in Topic Detection and Tracking”, Univ. of Helsiki, Dept. of CompSci, Aug. 19, 2003, used for background information only.
M. Andrade et al., “Automatic extraction of keywords from scientific text: application to the knowledge domain of protein families”, Protein Design Group, CNB-CSIC, May 15, 1998 used for background information only.
Roddick et al., “A Bibliography of Temporal, Spatial and Spatio-Termoral Data Mining Research”, Aug. 1999, ACM, used as background.
Ma et al., “Online Novelty Detection on Temporal Sequences”, 2003, ACM, used as background.

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