Automatic Genre Classification in Web Pages Applied to Web Comments
- Automatic Web comment detection could significantly facilitate information retrieval systems, e.g., a focused Web crawler. In this paper, we propose a text genre classifier for Web text segments as intermediate step for Web comment detection in Web pages. Different feature types and classifiers are analyzed for this purpose. We compare the two-level approach to state-of-the-art techniques operating on the whole Web page text and show that accuracy can be improved significantly. Finally, we illustrate the applicability for information retrieval systems by evaluating our approach on Web pages achieved by a Web crawler.
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Main Conference Proceedings of the 12th Konvens 2014
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| Author: | Melanie Neunerdt, Michael Reyer, Rudolf Mathar |
|---|---|
| URN: | https://nbn-resolving.org/urn:nbn:de:gbv:hil2-opus-2758 |
| Parent Title (English): | Proceedings of the 12th edition of the KONVENS conference |
| Document Type: | Conference Proceeding |
| Language: | English |
| Date of Publication (online): | 2014/10/23 |
| Release Date: | 2014/10/23 |
| Tag: | Informationsextraktion Information Extraction; Information Retrieval |
| GND Keyword: | Information Retrieval |
| First Page: | 145 |
| Last Page: | 151 |
| PPN: | Link zum Katalog |
| Contributor: | Faaß, Gertrud |
| Institutes: | Fachbereich III / Informationswissenschaft und Sprachtechnologie |
| DDC classes: | 400 Sprache / 400 Sprache, Linguistik |
| Collections: | KONVENS 2014 / Proceedings of the 12th KONVENS 2014 |
| Licence (German): |  Creative Commons - Namensnennung 3.0 |
