Method and system to compare data entities

Details Method and system to compare data entities Method and system to compare data entities

2008-01-15

2010-10-26

Breene, John E (Department: 2162)

Data processing: database and file management or data structures

Database and file access

Preparing data for information retrieval

C707S739000

Reexamination Certificate

active

07822750

ABSTRACT:
The present invention relates in general to methods and systems for comparing and maximizing the appropriateness of a first set of one or more data objects to a set of second data objects. In one embodiment, the first set of data objects represent one or more tasks to be fulfilled by a set of capabilities represented by the second data objects. In one embodiment, this invention provides an effective and accurate method and system to compare and maximize the appropriateness between the requirements of a task and the second set's capabilities, while these capabilities and requirements are contained, even if only latently, in data objects such as written documents, electronic databases or other sources of data and information. In one embodiment, topic modeling techniques are utilized to compare the data objects.

REFERENCES:
patent: 6351778 (2002-02-01), Orton et al.
patent: 6687696 (2004-02-01), Hofmann et al.
patent: 6728695 (2004-04-01), Pathria et al.
patent: 6917952 (2005-07-01), Dailey
patent: 6968332 (2005-11-01), Milic-Frayling et al.
patent: 7130837 (2006-10-01), Tsochantaridis et al.
patent: 7289985 (2007-10-01), Zeng et al.
patent: 7305389 (2007-12-01), Zeng et al.
patent: 7519201 (2009-04-01), Yang et al.
patent: 7681186 (2010-03-01), Chang et al.
patent: 2003/0182631 (2003-09-01), Tsochantaridis et al.
patent: 2007/0098254 (2007-05-01), Yang et al.
patent: 2007/0118498 (2007-05-01), Song et al.
patent: 2008/0140616 (2008-06-01), Encina et al.
patent: 2009/0234878 (2009-09-01), Herz et al.
Getoor et al. “A Latent Dirichlet Model for unsupervised Entity resolution”—SIAM International Conference on data Mining, 2006, (pp. 47-58).
Rhee et al. “Information Modelling for Adaptive Composition in Collaborative Work Environment”—International Journal 2005 (pp. 185-190).
Florent Money, Pedro Quelhas, Daniel Gatica-Perez, Jena-Marc Odobez, Constructing Visual Models with a Latent Space Approach, IDIAP Research Report 05-14, Feb. 2005, IDIAP Research Institute, Switzerland.
Darrell Laham, Winston Bennett, Jr., Thomas K. Landauer, An LSA-Based Software Tool for Matching Jobs, People, and Instruction, Interactive Learning Environments, 2000, vol. 8, No. 3, pp. 171-185, Swets&Zeitlinger, USA.
Blei, D., Ng, A. and Jordan, J. (2003). Latent Dirichlet allocation. Journal of Machine Learning Research, 3:993-1022, Jan. 2003, USA. http://www.cs.berkeley.edu/˜blei/papers/blei03a.pdf.
Hofmann, Thomas (1999). Probabilistic Latent Semantic Indexing, Proceedings of the 22nd Annual ACM Conference on Research and Development in Information Retrieval, USA. http://www.cs.brown.edu/people/th/papers/Hofmann-SIGIR99.pdf.
Hofmann, Thomas (2001). Unsupervised Learning by Probabilistic Latent Semantic Analysis. Machine Learning, 42:177-196, USA.
Steyvers, J. and Griffiths, T. (2003). Prediction and semantic association. Advances in Neural Information Processing Systems 15. USA.
Steyvers, J. and Griffiths, T. (2007). Probabilistic topic models. To appear in T. Landauer, D McNamara, S. Dennis, & W. Kintsch (eds), Latent Semantic Analysis: A road to meaning. Laurence Erlbaum, USA.
Palmer, M., Kingsbury, P. and Gildea, D. (2005) The Proposition Bank: An Annotated Corpus of Semantic Roles. Computational Linguistics, 31(1), 71-106, USA.
Sivic, J. Russell, B., Efros, A., Zisserman, A. and Freeman, W. (2005). “Discovering object categories in image collections.” Proc. Int'l Conf. Computer Vision, Beijing.
Griffiths, T.L., Steyvers, M., Blei, D.M. and Tenebaum, J.B.(2004) Integrating topics and syntax. Advances in Neural Information Processing Systems 17, USA.
Markus, M.P., Santorini, B., and Marcinkiewicz, M.A (1993) Building a Large Annotated Corpus of English: The Penn Treebank. Computational Linguistics, 19(2), 313-330, USA.
Griffiths, T.L., Steyvers, M., and Tenebaum, J.B. (2007). Topics in semantic representation. Psychological Review, vol. 114, No. 2, 211-244, USA.
Appelt, D.E. and Israel, David (1999). Introduction to Information Extraction Technology. International Joint Conference on Artificial Intelligence, Stockholm, Sweden.

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