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- W71514875 abstract "In this paper, we consider the problem of automatic Chinese Named Entity Recognition (NER) on web pages and try to extract the association between recognized entities. Usually NER approaches mainly focus on plain text and get poor results on the Web pages of Internet. In this paper, we first explore the difference of plain texts and web pages for NER. Based on characteristic of HTML structure, we propose a set of unified methods to recognize and associate entities on web pages. In our experiments, the F-measure of organization name recognition is 73.6%, where 14.3% improvement is achieved beyond the baseline system. The F-measure of organization name-address association on page level is 77.5%, and the performance achieves 89.5% on corpus level, which indicates that our approach is quite effective and practical." @default.
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- W71514875 date "2008-01-01" @default.
- W71514875 modified "2023-09-23" @default.
- W71514875 title "Chinese Organization Entity Recognition and Association on Web Pages" @default.
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- W71514875 doi "https://doi.org/10.1007/978-3-540-79396-0_2" @default.
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