Web object retrieval based on a language model

Data processing: database and file management or data structures – Database and file access – Preparing data for information retrieval

Reexamination Certificate

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C707S999006

Reexamination Certificate

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08001130

ABSTRACT:
A method and system is provided for determining relevance of an object to a term based on a language model. The relevance system provides records extracted from web pages that relate to the object. To determine the relevance of the object to a term, the relevance system first determines, for each record of the object, a probability of generating that term using a language model of the record of that object. The relevance system then calculates the relevance of the object to the term by combining the probabilities. The relevance system may also weight the probabilities based on the accuracy or reliability of the extracted information for each data source.

REFERENCES:
patent: 5594911 (1997-01-01), Cruz et al.
patent: 6076088 (2000-06-01), Paik et al.
patent: 6148349 (2000-11-01), Chow et al.
patent: 6266664 (2001-07-01), Russell-Falla et al.
patent: 6304864 (2001-10-01), Liddy et al.
patent: 6353825 (2002-03-01), Ponte
patent: 6418434 (2002-07-01), Johnson et al.
patent: 6418448 (2002-07-01), Sarkar
patent: 6493706 (2002-12-01), Mead et al.
patent: 6519580 (2003-02-01), Johnson et al.
patent: 6631369 (2003-10-01), Meyerzon et al.
patent: 6665665 (2003-12-01), Ponte
patent: 6965903 (2005-11-01), Agarwal et al.
patent: 6996778 (2006-02-01), Rajarajan et al.
patent: 7003511 (2006-02-01), Antonov
patent: 7003516 (2006-02-01), Dehlinger et al.
patent: 7058913 (2006-06-01), Siegel et al.
patent: 7231388 (2007-06-01), Matsubayashi et al.
patent: 7231395 (2007-06-01), Fain et al.
patent: 7529761 (2009-05-01), Wen et al.
patent: 7685197 (2010-03-01), Fain et al.
patent: 7720830 (2010-05-01), Wen et al.
patent: 2003/0220906 (2003-11-01), Chickering
patent: 2004/0034652 (2004-02-01), Hofmann et al.
patent: 2004/0080549 (2004-04-01), Lord et al.
patent: 2004/0181749 (2004-09-01), Chellapilla et al.
patent: 2005/0108200 (2005-05-01), Meik et al.
patent: 2006/0031211 (2006-02-01), Mizuno
patent: 2006/0074881 (2006-04-01), Vembu et al.
patent: 2006/0080353 (2006-04-01), Miloushev et al.
patent: 2006/0098871 (2006-05-01), Szummer
patent: 2006/0101060 (2006-05-01), Li et al.
patent: 2006/0167928 (2006-07-01), Chakraborty et al.
patent: 2006/0253437 (2006-11-01), Fain et al.
patent: 2007/0150486 (2007-06-01), Wen et al.
patent: 2010/0281009 (2010-11-01), Wen et al.
patent: WO 00/57311 (2000-09-01), None
patent: WO 00/73942 (2000-12-01), None
Arasu, Arvind and Hector Garcia-Molina, “Extracting Structured Data from Web Pages,” SIGMOD 2003, San Diego, © 2003 ACM, 12 pages.
Arlotta, Luigi et al., “Automatic Annotation of Data Extracted from Large Web Sites,” International Workshop on the Web and Databases, Jun. 2003, San Diego, 6 pages.
Balmin, Andrey, Vagelis Hristidis and Yannis Papakonstantinou, “ObjectRank: Authority-Based Keyword Search in Databases,” Proceedings of the 30th VLDB Conference, Toronto, Canada, 2004, 12 pages.
Berger, Adam L., Stephen A. Della Pietra and Vincent J. Della Pietra, “A Maximum Entropy Approach to Natural Language Processing,” Computational Linguistics, vol. 22, No. 1, © 1996 Association for Computational Linguistics, 36 pages.
Besag, Julian, “Spatial Interaction and the Statistical Analysis of Lattice Systems,” Journal of the Royal Statistical Society, Series B, vol. 36, No. 2, 1974, pp. 192-236.
Bunescu, Razvan C. and Raymond J. Mooney, “Relational Markov Networks for Collective Information Extraction,” Proceedings of the ICML 2004 Workshop on Statistical Relational Learning and its Connections to Other Fields (SLR-2004), Banff, Canada, Jul. 2004, 7 pages.
U.S. Appl. No. 11/305,500, Wen et al.
U.S. Appl. No. 11/461,400, Wen et al.
Buttler, David, Ling Liu and Calton Pu, “A Fully Automated Object Extraction System for the World Wide Web,” Proceedings of IEEE ICDCS-21, 2001, 11 pages.
Cai, Deng et al., “VIPS: a Vision-based Page Segmentation Algorithm,” Nov. 1, 2003, Microsoft Technical Report MSR-TR-2003-79, pp. 1-29.
Cai, Deng, Shipeng Yu, Ji-Rong Wen and Wei-Ying Ma, “Block-based Web Search,” SIGIR'04, Sheffield, South Yorkshire, UK, © 2004 ACM, 8 pages.
Chang, Chia-Hui and Shao-Chen Lui, “IEPAD: Information Extraction Based on Pattern Discovery,” WWW10, May, Hong Kong, © 2001 ACM, pp. 681-688.
Clarke, Charles L. A., “Controlling Overlap in Content-Oriented XML Retrieval,” SIGIR'05, Salvador, Brazil, © 2005 ACM, 8 pages.
Collins, Michael, “Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms,” 2002, 8 pages.
Collins, Micheal, “Ranking Algorithms for Named-Entity Extraction: Boosting and the Voted Perceptron,” Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics, Philadelphia, Jul. 2002, pp. 489-496.
Crescenzi, Valter, Giansalvatore Mecca and Paolo Merialdo, “RoadRunner: Towards Automatic Data Extraction from Large Web Sites,” Proceedings of the 27th VLDB Conference, Italy, 2001, 10 pages.
Embley, D.W., Y.S. Jian and Y.-K. Ng, “Record-Boundary Discovery in Web Documents,” In Proceedings of SIGMOD'99, 1999, pp. 1-24.
Fagin, Ronald et al., “Searching the Workplace Web,” WWW2003, Budapest, Hungary, ACM, 10 pages.
Fine, Shai, Yoram Singer and Naftali Tishby, “The Hierarchical Hidden Markov Model: Analysis and Applications,” Machine Learning, vol. 32, 1998, © 1998 Kluwer Academic Publishers, pp. 41-62.
Gravano, Luis and Hector Garcia-Molina, “Generalizing GLOSS to Vector-Space Databases and Broker Hierachies,” Proceedings of the 21st VLDB Conference, Zurich, Switzerland, 1995, 12 pages.
He, Xuming et al., “Multiscale Conditional Random Fields for Image Labeling,” Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 1-8.
Jensen, F. V., S. L. Lauritzen and K. G. Olesen, “Bayesian Updating in Causal Probabilistic Networks by Local Computations,” Computational Statistics Quarterly 4, 1990, © Physica-Verlag, pp. 269-282.
Kamps, Jaap et al., “Length Normalization in XML Retrieval,” SIGIR'04, Sheffield, South Yorkshire, UK, © 2004 ACM, 8 pages.
Kobayashi, Mei and Koichi Takeda, “Information Retrieval on the Web,” ACM Computing Surveys, vol. 32, No. 2, Jun. 2000, pp. 144-173.
Kschischang, Frank R., Brendan J. Frey and Hans-Andrea Loeliger, “Factor Graphs and the Sum-Product Algorithm,” IEEE Transactions on Information Theory, vol. 47, No. 2, Feb. 2001, © 2001 IEEE, pp. 498-519.
Kumar, Sanjiv and Martial Hebert, “Discriminative Fields for Modeling Spatial Dependencies in Natural Images,” Advances in Neural Information Processing Systems, NIPS 16, 2004, 8 pages.
Kumar, Sanjiv and Martial Hebert, “Discriminative Random Fields: A Discriminative Framework for Contextual Interaction in Classification,” Proceedings of the 2003 IEEE International Conference on Computer Vision, vol. 2, 2003, 8 pages.
Kushmerick, Nicholas, “Wrapper induction: Efficiency and expressiveness,” Mar. 10, 1999, Artificial Intelligence 118, 2000, © 2000 Elsevier Science B.V., pp. 15-68.
Laender, Alberto et al., “A Brief Survey of Web Data Extraction Tools,” ACM SIGMOD Record, 31 (2), 2002, 10 pages.
Lafferty, John, Andrew McCallum and Fernando Pereira, “Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data,” In Proceedings of ICML 2001, 8 pages.
Lalmas, Mounia, “Dempster-Shafer's Theory of Evidence applied to Structured Documents: modelling Uncertainty,” SIGIR 1997, Philadelphia, Pennsylvania, © 1997 ACM, pp. 110-118.
Leek, Timothy Robert, “Information Extraction Using Hidden Markov Models,” University of California, San Diego Computer Science Thesis Paper, 1997, 44 pages.
Lerman, Kristina et al., “Using the Structure of Web Sites for Automatic Segmentation of Table

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