Number of found records: 80
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Lie, D. H. |
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Sumatra: A system for Automatic Summary Generation |
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On line ( 15/06/2004) |
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This paper describes a system for automatic summary generation called Sumatra. It differs from other systems in being domain independent and, instead of relying on statistical techniques, it uses a Natural Language Processing approach, involving parsing, semantic analysis and text generation. The system has been evaluated by using final exam texts from the Dutch grammar school in summarizing. The main conclusion is that the Sumatra system is adequately capable of extracting the important information elements from a text. (AU) |
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Language Technology; Automatic Text Summarization; Natural Language Understanding |
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LIN, Chin-Yew; HOVY, Eduard |
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Identifying Topics by Position. |
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In Proceedings of the 5th Conference on Applied Natural Language Processing, pp.283-290. Association for Computational Linguistics, March 31 - April 3 1997. |
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This paper addresses the problem of identifying likely topics of texts by their position in the text. It describes the automated training and evaluation of an Optimal Position Policy, a method of locating the likely positions of topic-bearing sentences based on genre-specific regularities of discourse structure. This method can be used in applications such as information retrieval, routing, and text summarization. (AU) |
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summarization; evaluation; information retrieval; discourse structure |
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MARCU, Daniel |
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The Automatic Construction of Large-Scale Corpora for Summarization Research. |
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In HEARST, M., GEY. F., TONG, R., (Eds), Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp 137-144, University of California, Berkely, August 1999. |
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On line ( 07/2005) (Only UGR) |
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Summarization research is notorious for its lack of adequate corpora: today, there exist only a few small collections of texts whose units have been manually annotated for textual importance. Given the cost and tediousness of the annotation process, it is very unlikely that we will ever manually annotate for textual importance sufficiently large corpora of texts. To circumvent this problem, we have developed an algorithm that constructs such corpora automatically. Our algorithm takes as input an Abstract, Texti tuple and generates the corresponding Extract, i.e., the set of clauses (sentences) in the Text that were used to write the Abstract. The performance of the algorithm is shown to be close to that of humans by means of an empirical experiment. The experiment also suggests extraction strategies that could improve the performance of automatic summarization systems. (AU) |
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information system; document; summarization |
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MAYNARD, Diana; BONTCHEVA, Kalina; SAGGION, Horacio; CUNNINGHAM, Hamish; HAMZA, Oana |
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Using a Text Engineering Framework to Build an Extendable and Portable IE-based Summarisation System. |
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In Proceedings of the 39th Meeting of the Association for Computational Linguistics, July 6-13 2002 |
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In this paper we show how tools provided by a text engineering framework (GATE) have been used to build an IE-based summarisation system in the domain of occupational health and safety. The core of the application is based on pattern-action grammar rules, which can easily be extended or ported to new domains. The GATE framework was also used to evaluate automatically the system's performance. (AU) |
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summarization; Information Extraction; GATE; evaluation |
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