Rule based autonomous citation mining with TIERL
Citations management is an important task in managing digital libraries. Citations provide valuable information e.g., used in evaluating an author’s influences or scholarly quality (the impact factor of research journals). But although a reliable and effective autonomous citation management is essen...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Journal of Digital Information Management
2006
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/542/ http://ir.unimas.my/id/eprint/542/1/Rule_based_Autonomous_Citation_Mining_with_TIERL.pdf |
| _version_ | 1848834564922802176 |
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| author | Muhammad Tanvir, Afzal Maurer, Hermann Balke, Wolf-Tilo Narayanan, Kulathuramaiyer |
| author_facet | Muhammad Tanvir, Afzal Maurer, Hermann Balke, Wolf-Tilo Narayanan, Kulathuramaiyer |
| author_sort | Muhammad Tanvir, Afzal |
| building | UNIMAS Institutional Repository |
| collection | Online Access |
| description | Citations management is an important task in managing digital libraries. Citations provide valuable information e.g., used in evaluating an author’s influences or scholarly quality (the impact factor of research journals). But although a reliable and effective autonomous citation management is essential, manual citation management can be extremely costly. Automatic citation mining on the other hand is a non-trivial task mainly due to non-conforming citation styles, spelling errors and the difficulty of reliably extracting text from PDF documents. In this paper we propose a novel rule-based autonomous citation mining technique, to address this important task. We define a set of common heuristics that together allow to improve the state of the art in automatic citation mining. Moreover, by first disambiguating citations based on venues, our technique significantly enhances the correct discovery of citations. Our experiments show that the proposed approach is indeed able to overcome limitations of current leading citation indexes such as ISI Web of Knowledge, Citeseer and Google Scholar. |
| first_indexed | 2025-11-15T05:53:59Z |
| format | Article |
| id | unimas-542 |
| institution | Universiti Malaysia Sarawak |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T05:53:59Z |
| publishDate | 2006 |
| publisher | Journal of Digital Information Management |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | unimas-5422016-04-12T06:43:45Z http://ir.unimas.my/id/eprint/542/ Rule based autonomous citation mining with TIERL Muhammad Tanvir, Afzal Maurer, Hermann Balke, Wolf-Tilo Narayanan, Kulathuramaiyer T Technology (General) Z665 Library Science. Information Science Citations management is an important task in managing digital libraries. Citations provide valuable information e.g., used in evaluating an author’s influences or scholarly quality (the impact factor of research journals). But although a reliable and effective autonomous citation management is essential, manual citation management can be extremely costly. Automatic citation mining on the other hand is a non-trivial task mainly due to non-conforming citation styles, spelling errors and the difficulty of reliably extracting text from PDF documents. In this paper we propose a novel rule-based autonomous citation mining technique, to address this important task. We define a set of common heuristics that together allow to improve the state of the art in automatic citation mining. Moreover, by first disambiguating citations based on venues, our technique significantly enhances the correct discovery of citations. Our experiments show that the proposed approach is indeed able to overcome limitations of current leading citation indexes such as ISI Web of Knowledge, Citeseer and Google Scholar. Journal of Digital Information Management 2006 Article NonPeerReviewed text en http://ir.unimas.my/id/eprint/542/1/Rule_based_Autonomous_Citation_Mining_with_TIERL.pdf Muhammad Tanvir, Afzal and Maurer, Hermann and Balke, Wolf-Tilo and Narayanan, Kulathuramaiyer (2006) Rule based autonomous citation mining with TIERL. Journal of Digital Information Management, 8 (3). pp. 196-204. |
| spellingShingle | T Technology (General) Z665 Library Science. Information Science Muhammad Tanvir, Afzal Maurer, Hermann Balke, Wolf-Tilo Narayanan, Kulathuramaiyer Rule based autonomous citation mining with TIERL |
| title | Rule based autonomous citation mining with TIERL |
| title_full | Rule based autonomous citation mining with TIERL |
| title_fullStr | Rule based autonomous citation mining with TIERL |
| title_full_unstemmed | Rule based autonomous citation mining with TIERL |
| title_short | Rule based autonomous citation mining with TIERL |
| title_sort | rule based autonomous citation mining with tierl |
| topic | T Technology (General) Z665 Library Science. Information Science |
| url | http://ir.unimas.my/id/eprint/542/ http://ir.unimas.my/id/eprint/542/1/Rule_based_Autonomous_Citation_Mining_with_TIERL.pdf |