Practical Approach to Automatic Text Summarization
||Hynek, Jiri and Jezek, Karel
||Practical Approach to Automatic Text Summarization
||ELPUB2003. From information to knowledge: Proceedings of the 7th ICCC/IFIP International Conference on Electronic Publishing held at the Universidade do Minho, Portugal 25-28 June 2003/Edited by: Sely Maria de Souza Costa, João Álvaro Carvalho, Ana Alice Baptista, Ana Cristina Santos Moreira. Universidade do Minho, 2003.
||The significance of automatic document summarization increases with the threat of information overload we are facing. Short summaries can be presented to users, for example, in place of fulllength documents found by a search engine in response to a user’s query. We have analyzed variousapproaches to document summarization, using some existing algorithms and combining these with a novel use of itemsets. The resulting summarizer is evaluated by comparing classification of original documents and that of abstracts generated automatically. Despite highly promising results achieved by this evaluation, readability of abstracts must be further improved by integrating additional heuristic approaches.
||document summarization, summarizer, condensation, abstract, abstracting, extraction, text, machine learning, classification, categorization, sentence selection, highlight, classifier, heuristics, itemsets, term frequency, evaluation
||file.pdf (215,710 bytes)
Post discussion ...
These pages are best viewed with any standards compliant browser (e.g. Mozilla).