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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Sanyuan Gao Si Li Weiran Xu Jun Guo |
| Copyright Year | 2010 |
| Abstract | Cross-document coreference resolution plays an import part in the filed of natural language processing (NLP). It captures the ability of gathering documents for information about a certain entity. Most previous algorithms identify the underlying entity of a given document depending on the original text, which is unreliable if the original text contains multiple parts of different themes. In this paper, we propose a cross-document coreference resolution algorithm based on automatic text summary instead of the original text. In our approach, we extract query-specific and informative-indicative summary from the original text by using Hobbs algorithm and measure the similarity between two summaries. This automatic text summary-based cross-document coreference resolution (ATSCDCR) system is effective in disambiguating different entities of the same mention name and identifying the same entity of different mention names. The results from our experiments show that the macro average of ATSCDCR system is up to 73.16% and the micro average of ATSCDCR system is 67.34 %. |
| Starting Page | 306 |
| Ending Page | 309 |
| File Size | 282314 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424453979 |
| e-ISBN | 9781424453986 |
| DOI | 10.1109/WKDD.2010.56 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-01-09 |
| Publisher Place | Thailand |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Biomedical informatics Cross-Document Coreference Resolution Named Entity Type Recognition Displays Automatic Text Summary Pattern recognition Electronic mail Data mining Hobbs Algorithm Text recognition Natural language processing Joining processes Intelligent systems Testing |
| Content Type | Text |
| Resource Type | Article |
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