Systems and methods for displaying interactive topic-based...

Data processing: presentation processing of document – operator i – Presentation processing of document – Layout

Reexamination Certificate

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

C704S009000, C704S257000

Reexamination Certificate

active

07117437

ABSTRACT:
Techniques for displaying interactive topic-based summarization are provided. A text to be summarized is segmented. Discrete keyword, key-phrase, n-gram, sentence and other sentence constituent based summaries are generated based on statistical measures for each text segment. Interactive topic-based summaries are displayed with human sensible omitted text indicators such as alternate colors, fonts, sounds, tactile elements or other human sensible display characteristics useful in indicating omitted text. Individual and/or combinations of discrete keyword, key-phrase, n-gram, sentence, noun phrase and sentence constituent based summaries are dynamically displayed to provide an overview of topic and subtopic development within a text. A hierarchical and interactive display of texts based on the use of discrete sentence constituent based summaries which associates expansible and contractible displayed text to provide contextualized access to an interactive topic-based text summary and to an original text.

REFERENCES:
patent: 5384703 (1995-01-01), Withgott et al.
patent: 5418951 (1995-05-01), Damashek
patent: 5442778 (1995-08-01), Pedersen
patent: 5689716 (1997-11-01), Chen
patent: 5708825 (1998-01-01), Sotomayor
patent: 5745602 (1998-04-01), Chen et al.
patent: 5778397 (1998-07-01), Kupiec et al.
patent: 5806021 (1998-09-01), Chen et al.
patent: 5838323 (1998-11-01), Rose et al.
patent: 5918240 (1999-06-01), Kupiec et al.
patent: 6052657 (2000-04-01), Yamron et al.
patent: 6128634 (2000-10-01), Golovchinsky et al.
patent: 6205456 (2001-03-01), Nakao
patent: 6289304 (2001-09-01), Grefenstette
patent: 6775677 (2004-08-01), Ando et al.
patent: 6963830 (2005-11-01), Nakao
patent: 6968332 (2005-11-01), Milic-Frayling et al.
patent: 7017114 (2006-03-01), Guo et al.
patent: 2002/0138528 (2002-09-01), Gong et al.
patent: 2003/0182631 (2003-09-01), Tsochantaridis et al.
patent: 2004/0044519 (2004-03-01), Polanyi et al.
patent: 2004/0117725 (2004-06-01), Chen et al.
patent: 2004/0122657 (2004-06-01), Brants et al.
patent: 2004/0225667 (2004-11-01), Hu et al.
patent: 2005/0091203 (2005-04-01), Liu et al.
Chin-yew Lin & Eduard Hovy, Identifying Topics by Position, 1997, CiteSeer, pp. 283-290.
Achim Hoffman & Son Bao Pham, Towards topic-based summarization for interactive document viewing, 2003, ACM Press, pp. 28-35.
Caterina Caracciolo, willem van Hage, and Marrten de Rijke, Towards a Topic Driven Access to Full Text Documents, CiteSeer, pp. 1-5.
Doug Beeferman, Adam Berger and John Lafferty, Statistical Models for Text Segmentation, 1999, CiteSeer, pp. 1-37.
Jay M. Ponte and W. Bruce Croft, Text Segmentation by Topic, 1997, CiteSeer, pp. 1-13.
Gael Dias, Elsa Alves and Celia Nunes, Topic Segmentation: How Much Can We Do By Counting Words And Sequences of Words, 2005, pp. 1-28.
Jaime G. Carbonnell et al., “The use of MMR, diversity-based reranking for reordering documents and producing summaries” In Research and Development in Information Retrieval, SIGIR-98, pp. 335-336, 1998.
B-W Chang et al., “Fluidly revealing information in fluid documents”, In Proceedings of Smart Graphics 2000, AAAI Spring Symposium, Stanford University, 2000.
Freddy Y. Y. Choi et al., “Latent Semantic Analysis for Text Segmentation” In Proceedings of the 2001 Conference on Empirical Methds in Natural Language Processing. pp. 109-117, 2001.
D. Cutting et al., “Scatter/Gather: A cluster-based approach to browsing large document collections”, In Proceedings of SIGIR-92, 1992.
A. P. Dempster et al., Maximum Likelihood from incomplete data via the em algorithm, Journal of the Royal Statistical Society, 39(1):1-21, 1977.
Dan Gildea et al., “Topic based language models using em”, In Proceedings of the 6th European Conference on Speech Communication and Technology,(Eurospeech'99). Budapest, Hungary, 1999.
Marti A. Hearst, “Texttiling: Segmenting text into multi-paragraph subtopic-passages”, In Computional Linguistics, 23(1):33-64, 1997.
Thomas Hoffmann, “Probabalistic latent semantic indexing”, In Proceedings of SIGIR-99, pp. 35-44, Berkeley, CA, 2000.
D. House, “Interactive Text Summarization for fast answers”, printed from http://www.mitre.org/pubs/edge/july—97/first.htm on Nov. 25, 2002.
H. Jing, “Sentence simplification in automatic text summarization”, In Proceedings of the 6th Applied Natural Language Processing Conference ((ANLP)-00), Seattle, WA, 2000.
Kevin Knight et al., “Statistics-based summarization—step one: Sentence compression”, In Proceedings of the AAAI, pp. 703-710, 2000.
W. Kraaij et al. “Combining a mixture language model and naive bayes for multi-document summarisation”, In Proceedings of the DUC-2001, New Orleans, LA 2001.
Bruce Krulwich et al., “Learning user information interests through the extraction of semantically significant phrases”, In AAAI Spring Symposium on Machine Learning in Information Access, 1996.
Julian Kupiec et al. “A trainable document summarizer”, In Proceedings of SIGIR, 1995.
Hang Li et al., “Topic Analysis using a finite mixture model”, IPSJ SIGNotes Natural Language, (NL), 139(009), 2000.
C. Y. Lin et al., “The automated acquisition of topic signatures for text summarization”, In Proceedings of COLING-2000, Strasbourg, France, 2000.
Andrew McCallum et al., “A comparison of event models for naive bayes text classification”, In AAAI-98 Workshop of Learning for Text Categorization, Madison, WI, USA. 1998.
A. M. Steier et al., “Exporting Phases: A statistical analysis of topical language”, In 2d Symposium on Document Analysis and Information Retrieval, pp. 179-190, 1993.
Peter Turney et al., “Extraction of keyphrases from text: Evaluation of four algorithms”, In Technical Report NRC-41550, National Research Council, Canada, 1997.
Peter Turney et al., “Learning algorithms for keyphrase extraction”, In Information Retrieval, 2(4):303-336, 2000.
M. Witbrock et al., Headline generation: A framework for generating highly-condensed non-extractive summaries, In Proceedings of the SIGIR-99, pp. 315-316, Berkeley, CA 1999.
Ian H. Witten et al., “KEA: Practical automatic keyphrase extraction”, In Proceedings of the Fourth ACM Conference on Digital Libraries, 1999.
B. Borguraev et al., “Discourse Segmentation in Aid of Document Summarization” In Proceedings of the Hawaii International Conference on System Sciences., IEEE, 2000.
T. Strzalkowski et al., “A Robust Practical Text Summarization System”, In Advances in Automatic Text Summarization by Inderjeet Mani and Mark Maybury, 1999.
T. Brants et al. “Arabic Document Topic Analysis”, in Proceedings of Arabic Language Resources and Evaluation: Status and Prospects, LREC-2002, Las Palmas, Spain, 2002.
Barzilay et al., “Using Lexical Chains for Text Summarization” in Advances in Automatic Text Summarization, MIT Press, Cambridge MA, 1999.
O. Buyukkokten et al., “Seeing the Whole in Parts: Text Summarization for web browsing on hand-held devices”, in the 10th International WWW Conf. p. 652-662, Hong Kong, China, 2001.
P. Zellweger et al., “Fluid Links for informed and incremental link transitions” in UK Conference on Hypertext, pp. 50-57, 1998.
T. Kailith, “The Divergence and Bhattacharyya Distance Measures in Signal Selection”, in IEEE Trans. on COmmunication Technology 15-1, Feb. 1967, pp. 52-60.
Y. Xie et al., “Locality in Search Engine Queries and Its Implications for Caching”, IEEE Infocom 2002.

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Systems and methods for displaying interactive topic-based... does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Systems and methods for displaying interactive topic-based..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Systems and methods for displaying interactive topic-based... will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-3622891

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.