Number of found records: 11
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SAGGION, Horacio |
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Using Linguistic Knowledge in Automatic Abstracting |
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37th Annual Meeting of the Association for Computational Linguistics 1999 |
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We present work on the automatic generation of short indicative-informative abstracts of scientific and technical articles. The indicative part of the abstract identifies the topics of the document while the informative part of the abstract elaborate some topics according to the reader's interest by motivating the topics, describing entities and defining concepts. We have defined our method of automatic abstracting by studying a corpus professional abstracts. The method also considers the reader's interest as essential in the process of abstracting. (AU) |
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automatic generation abstracts; scientific and technical article |
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SALTON, Gerard; ALLAN, James; SINGHAL, Amit |
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Automatic text decomposition and structuring |
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Information Processing and Management, 1996, vol. 32, n.2, pp.127-138 |
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On line ( 16/02/2005)(Only UGR) |
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Sophisticated text similarity measurements are used to determine relationships between natural language text and text excerpts. The resulting linked hypertext maps can be decomposed into text segments and text theme, and these decompositions are usable to identify different text types and text structures, leading to improved text access and utilization. Gives examples of text decomposition for expository and non expository texts. (AU) |
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Automatic text analysis; Natural language processing |
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DELORT, J.Y.; BOUCHON-MEUNIER, B.; RIFQI, M. |
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Enhanced web document summarization using hyperlinks. |
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In Proceedings of the 14th ACM conference on Hypertext and Hypermedia, pp.208-215. ACM Press, 2003. |
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This paper addresses the issue of Web document summarization. As textual content of Web documents is often scarce or irrelevant and existing summarization techniques are based on it, many Web pages and websites cannot be suitably summarized. We consider the context of a Web document by the textual content of all the documents linking to it. To summarize a target Web document, a context-based summarizer has to perform a preprocessing task, during which it will be decided which pieces of information in the source documents are relevant to the content of the target. Then a context-based summarizer faces two issues: first, the selected elements may partially deal with the topic of the target, second they may be related to the target and yet not contain any clues about the content of the target. In this paper we put forward two new summarization by context algorithms. The first one uses both the content and the context of the document and the second one is based only on the elements of the context. It is shown that summaries taking into account the context are usually much more relevant than those made only from the content of the target document. Optimal conditions of the proposed algorithms with respect to the sizes of the content and the context of the document to summarize are studied. (AU) |
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Summarization; Web document; Hyperlinks; Context. |
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