On discovering concept entities from web sites
A web site usually contains a large number of concept entities, each consisting of one or more web pages connected by hyperlinks. In order to discover these concept entities for more expressive web site queries and other applications, the web unit mining problem has been proposed. Web unit mining ai...
| Main Authors: | , , |
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| Format: | Conference Paper |
| Language: | English |
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2009
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| Online Access: | https://hdl.handle.net/10356/91291 http://hdl.handle.net/10220/6122 |
| _version_ | 1811691070502731776 |
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| author | Yin, Ming Goh, Dion Hoe-Lian Lim, Ee Peng |
| author2 | Wee Kim Wee School of Communication and Information |
| author_facet | Wee Kim Wee School of Communication and Information Yin, Ming Goh, Dion Hoe-Lian Lim, Ee Peng |
| author_sort | Yin, Ming |
| collection | NTU |
| description | A web site usually contains a large number of concept entities, each consisting of one or more web pages connected by hyperlinks. In order to discover these concept entities for more expressive web site queries and other applications, the web unit mining problem has been proposed. Web unit mining aims to determine web pages that constitute a concept entity and classify concept entities into categories. Nevertheless, the performance of an existing web unit mining algorithm, iWUM, suffers as it may create more than one web unit (incomplete web units) from a single concept entity. This paper presents a new web unit mining algorithm, kWUM, which incorporates site-specific knowledge to discover and handle incomplete web units by merging them together and assigning correct labels. Experiments show that the overall accuracy has been significantly improved. |
| first_indexed | 2024-10-01T06:14:03Z |
| format | Conference Paper |
| id | ntu-10356/91291 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:14:03Z |
| publishDate | 2009 |
| record_format | dspace |
| spelling | ntu-10356/912912020-03-07T12:15:48Z On discovering concept entities from web sites Yin, Ming Goh, Dion Hoe-Lian Lim, Ee Peng Wee Kim Wee School of Communication and Information International Conference on Computational Science and its Applications (5th : 2005 : Singapore) DRNTU::Engineering::Computer science and engineering::Computer systems organization::Computer-communication networks A web site usually contains a large number of concept entities, each consisting of one or more web pages connected by hyperlinks. In order to discover these concept entities for more expressive web site queries and other applications, the web unit mining problem has been proposed. Web unit mining aims to determine web pages that constitute a concept entity and classify concept entities into categories. Nevertheless, the performance of an existing web unit mining algorithm, iWUM, suffers as it may create more than one web unit (incomplete web units) from a single concept entity. This paper presents a new web unit mining algorithm, kWUM, which incorporates site-specific knowledge to discover and handle incomplete web units by merging them together and assigning correct labels. Experiments show that the overall accuracy has been significantly improved. Accepted version 2009-10-02T01:34:21Z 2019-12-06T18:03:02Z 2009-10-02T01:34:21Z 2019-12-06T18:03:02Z 2005 2005 Conference Paper Yin, M., Goh, D., & Lim, E. P. (2005). On discovering concept entities from web sites. Proceedings of the International Conference on Computational Science and its Applications 2005 ICCSA 2005, (May 9-12, Singapore), Lecture Notes in Computer Science 3481, 1177- 1186. https://hdl.handle.net/10356/91291 http://hdl.handle.net/10220/6122 10.1007/11424826_125 en The original publication is available at www.springerlink.com. 12 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering::Computer systems organization::Computer-communication networks Yin, Ming Goh, Dion Hoe-Lian Lim, Ee Peng On discovering concept entities from web sites |
| title | On discovering concept entities from web sites |
| title_full | On discovering concept entities from web sites |
| title_fullStr | On discovering concept entities from web sites |
| title_full_unstemmed | On discovering concept entities from web sites |
| title_short | On discovering concept entities from web sites |
| title_sort | on discovering concept entities from web sites |
| topic | DRNTU::Engineering::Computer science and engineering::Computer systems organization::Computer-communication networks |
| url | https://hdl.handle.net/10356/91291 http://hdl.handle.net/10220/6122 |
| work_keys_str_mv | AT yinming ondiscoveringconceptentitiesfromwebsites AT gohdionhoelian ondiscoveringconceptentitiesfromwebsites AT limeepeng ondiscoveringconceptentitiesfromwebsites |