Number of found records: 80
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Zajic, David M.; Dorr, Bonnie J.; Lin, Jimmy |
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Single-Document and Multi-Document Summarization Techniques for Email Threads Using Sentence Compression |
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Information Processing and Management, 2008, vol. 44, n. 4, pp. 1600-1610 |
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On line |
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We present two approaches to email thread summarization: collective message summarization (CMS) applies a multi-document summarization approach, while individual message summarization (IMS) treats the problem as a sequence of single-document summarization tasks. Both approaches are implemented in our general framework driven by sentence compression. Instead of a purely extractive approach, we employ linguistic and statistical methods to generate multiple compressions, and then select from those candidates to produce a final summary. We demonstrate these ideas on the Enron email collection - a very challenging corpus because of the highly technical language. Experimental results point to two findings: that CMS represents a better approach to email thread summarization, and that current sentence compression techniques do not improve summarization performance in this genre (AU) |
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Automatic abstracting; Electronic mail |
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Zajic, David; Dorr, Bonnie J.; Lin, Jimmy; Schwartz, Richard |
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Multi-candidate reduction: Sentence compression as a tool for document summarization tasks |
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Information Processing & Management, Nov2007, Vol. 43 Issue 6, p1549-1570 |
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On line (04/2008) (Only UGR) |
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This article examines the application of two single-document sentence compression techniques to the problem of multi-document summarization-a "parse-and-trim" approach and a statistical noisy-channel approach. We introduce the multi-candidate reduction (MCR) framework for multi-document summarization, in which many compressed candidates are generated for each source sentence. These candidates are then selected for inclusion in the final summary based on a combination of static and dynamic features. Evaluations demonstrate that sentence compression is a valuable component of a larger multi-document summarization framework (DB) |
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Automatic abstracts |
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Indexing digital documents |
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On line (11/05/2005) |
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Conversion from paper-based filing to an electronic document management system (EDMS) requires significant planning. Indexing digital documents is not optional. This paper distinguishes between field-based and full-text indexing and recommends a combination of the two. Tangible and intangible organizational benefits of indexing digital documents are outlined. The various costs associated with indexing are detailed, and specific price information from service bureaus is presented. Recommendations for choosing an EDMS are included, as well as a model for assessing the organization's indexing needs. (Web) |
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indexing; digital document; full-text indexing; field-based indexing; EDMS |
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ANGHELUTA, Roxana; MITA, Rudradeb; JING, Xiuli; et al. |
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K. U. Leuven summarization system DUC 2004 |
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PDF |
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Presentation of methods, results and discussion of the results of the DUC activities with participation of the authors |
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method; abstract; multidocument; DUC |
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