Systems and methods for new event detection

Data processing: database and file management or data structures – Database design – Data structure types

Reexamination Certificate

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Reexamination Certificate

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07577654

ABSTRACT:
Techniques for new event detection are provided. For a new story and a corpus of stories, story-pairs based on the new story and each corpus story are determined. Adjustments to the importance of terms are determined based on story characteristics associated with each story. Story characteristics are based on direct or indirect characteristics. Direct story characteristics include authorship, language associated with a story and the like. Indirect story characteristics may include derived characteristics such as an ROI category characteristic, a same ROI characteristic, a same event-same source characteristic, an average story similarity characteristic or any other known or later developed characteristic associated with a story. Adjustments to the inter-story similarity metrics are then determined based on story characteristics and/or a weighting function. New event scores and/or new event categorizations for stories are determined based on the inter-story similarity metrics and the adjustments based on the story characteristics. Optionally new events are selected based on new event scores and a threshold value.

REFERENCES:
patent: 5835905 (1998-11-01), Pirolli et al.
patent: 6012073 (2000-01-01), Arend et al.
patent: 6131089 (2000-10-01), Campbell et al.
patent: 6192360 (2001-02-01), Dumais et al.
patent: 6411962 (2002-06-01), Kupiec
patent: 6584220 (2003-06-01), Lantrip et al.
patent: 6606620 (2003-08-01), Sundaresan et al.
patent: 6961954 (2005-11-01), Maybury et al.
patent: 7085755 (2006-08-01), Bluhm et al.
patent: 2002/0059602 (2002-05-01), Macrae et al.
patent: 2003/0182631 (2003-09-01), Tsochantaridis et al.
patent: 2004/0002849 (2004-01-01), Zhou
patent: 2004/0006559 (2004-01-01), Gange et al.
patent: 2005/0021490 (2005-01-01), Chen et al.
patent: 2006/0062451 (2006-03-01), Li et al.
Title: Interim Guidelines for Examination of Patent Applications for Patent Subject Matter Eligibility; Annex IV; pp. 50-57; Publication Date: Nov. 22, 2005.
Author: Allan et al; Title: Topic Detection and Tracking Pilot Study Final Report; Date: 1998; Publisher: Darpa; Website: http://www.itl.nist.iaui/894.01/publications/darpa98/pdf/tdt2040.pdf.
Allan, J. et al., “Detection, Bounds, and Timelines: UMass and TDT-3” in Proceedings of Topic Detection and Tracking Workshop (TDT-3), Vienna, Virgina, Feb. 2000.
Allan, J. et al., “On-line new event detection and tracking” in Proceedings of SIGIR-98, Melbourne, Australia, 1998, p. 37-45.
Allan, J., et al., “Topic-based novelty detection”, Summer Workshop Final Report, Center for Language and Speech Processing, John Hopkins University, 1999.
Franz, M., et al., “First Story Detection: Combining similarity and novelty-based approaches”, Slides at the TDT-2001 meeting, IBM, 2001.
Brants, T., et al., “Topic based document segmentation with probablistic latent semantic analysis”, in International Conference on Information and Knowledge Management (CIKM), McLean, VA 2002.
Croft, W.B., et al., “Relevance feedback and personalization: A language modelling perspective” in DELOS Workshop: Personalisation and Recommender Systems in Digital Libraries, 2001.
Dunning, T.E., “Accurate Methods for the statistics of surprise and coincidence” in Computational Linguistics 19(1):61-74, 1993.
Hearst, M.A., “TextTiling: Segmenting text into multi-paragraph subtopic passages”, in Computational Linguistics, 23(1):33-64, 1997.
Joachims, T., “Making large-scale svm learning practical”, in Advances in Kernel-Methods Support Vector Learning, B. Schlkopf, C. Burges, A. Smola eds., MIT Press, 1999.
Joachims, T., “Text categorization with support vector machines: learning with many relevant features” in Proceedings of the 10th European Conference on Machine Learning, 1998, pp. 137-142.
Lavrenko, V., et al., “Relevance models for topic detection and tracking”, in Proceedings of the HLT-2002, San Diego, CA 2002.
Schapire, R. E., et al., Boostexter: A boosting-based system for text categorization, in Machine Learning, 2000.
Yang, Y., et al., “A study on retrospective and on-line event detection”, in Proceedings of SIGIR-98, Melbourne, Australia, 1998.
Yang, Y., et al., “Topic-conditioned novelty detection” in Proceedings of the International Conference on Knowledge Discovery and Data Mining, Edmonton, Canada, 2002.
Zhang, Y., et al., “Novelty and redundancy detection in adaptive filtering” in Proceedings of SIGIR-02, Tampere, Finland, 2002, pp. 81-88.
R. O. Duda, P.E. Hart and D. G. Stark, Pattern Classification, Second Edition, Jon Wiley & Sons Inc. New York, 2001, p. 630-633.
Ralf D. Brown, “Dynamic Stopwording for Story Link Detection”, Language Technologies Institute Carnegie Mellon University, Proceedings of the HLT 2002: Second Conference on Human Language Technology Research, San Diego, CA Mar. 25, 2002.

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