Document summarization based on topicality and specificity

Details Document summarization based on topicality and specificity Document summarization based on topicality and specificity

2008-03-18

2008-03-18

Harper, V. Paul (Department: 2626)

Data processing: speech signal processing, linguistics, language

Linguistics

Natural language

C704S007000

Reexamination Certificate

active

10699375

ABSTRACT:
Topicality scores are determined for a number of phrasal expressions in documents. Phrasal expressions may be noun phrases, with or without corresponding prepositional phrases, subject-verb pairs, and verb-object pairs. The documents describe some topic or multiple topics. Techniques can be used to determined how the phrasal expression compares with the topic or topics being described in the documents. Specificities are determined for the phrasal expressions. Techniques may be used to determine whether phrasal expressions are more or less specific than other phrasal expressions. An order is determined for the phrasal expressions by using the topicality scores and the specificities. The order may be represented as a phrasal expression tree, for example. The phrasal expression tree may be displayed to a user, and the user can navigate through the phrasal expression tree, and therefore through the one or more documents.

REFERENCES:
patent: 6865572 (2005-03-01), Boguraev et al.
patent: 2002/0138528 (2002-09-01), Gong et al.
Fleischman et al. “Fine Grained Classification of Named Entities” Coling 2002.
Goldstein et al. “Summarizing Text Documents: Sentence Selection and Evaluation Metrics” SIGIR 1999.
Muresan et al. “Combining Linguistic and Machine Learning Techniques for Email Summarization” Proceedings of CoNII-2001, Toulouse, France.
White et al. (“Multidocument Summarization via Information Extraction” In the proceedings of the First International Conference on Human Language Technology Research, 2001, San Diego, CA.
Ando et al., “Iterative Residual Rescaling: An Analysis and Generalization of LSI,” SIGIR, pp. 154-162 (2001).
Boguraev et al., “Discourse Segmentation in Aid of Document Summarization,” Proc. OfHawaaii Inter'l Conf. On System Summaries (2000).
Deerwester et al., “Indexing by Latent Semantic Analysis,” Journal of American Society for Information Science, vol. 41, No. 6, pp. 391-407 (1990).
Radev et al., “Generating Natural Language Summaries from Multiple On-Line Sources,” Association for Computational linguistics (1998).

Affiliated with

Also associated with

Rating

Document summarization based on topicality and specificity does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Document summarization based on topicality and specificity, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Document summarization based on topicality and specificity will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFUS-PAI-O-3918341