Conference
When topic models disagree: keyphrase extraction with mulitple topic models
| العنوان: | When topic models disagree: keyphrase extraction with mulitple topic models |
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| المؤلفون: | Sterckx, Lucas, Demeester, Thomas, Deleu, Johannes, Develder, Chris |
| المصدر: | WWW'15 COMPANION: PROCEEDINGS OF THE 24TH INTERNATIONAL CONFERENCE ON WORLD WIDE WEB ; ISBN: 978-1-4503-3473-0 |
| سنة النشر: | 2015 |
| المجموعة: | Ghent University Academic Bibliography |
| مصطلحات موضوعية: | Technology and Engineering, IBCN |
| الوصف: | We explore how the unsupervised extraction of topic-related keywords benefits from combining multiple topic models. We show that averaging multiple topic models, inferred from different corpora, leads to more accurate keyphrases than when using a single topic model and other state-of-the-art techniques. The experiments confirm the intuitive idea that a prerequisite for the significant benefit of combining multiple models is that the models should be sufficiently different, i.e., they should provide distinct contexts in terms of topical word importance. |
| نوع الوثيقة: | conference object |
| وصف الملف: | application/pdf |
| اللغة: | English |
| ردمك: | 978-1-4503-3473-0 1-4503-3473-3 |
| Relation: | https://biblio.ugent.be/publication/5974210; http://hdl.handle.net/1854/LU-5974210; http://doi.org/10.1145/2740908.2742731; https://biblio.ugent.be/publication/5974210/file/5974211 |
| DOI: | 10.1145/2740908.2742731 |
| الاتاحة: | https://biblio.ugent.be/publication/5974210 http://hdl.handle.net/1854/LU-5974210 https://doi.org/10.1145/2740908.2742731 https://biblio.ugent.be/publication/5974210/file/5974211 |
| Rights: | No license (in copyright) ; info:eu-repo/semantics/openAccess |
| رقم الانضمام: | edsbas.28C8027 |
| قاعدة البيانات: | BASE |
| ردمك: | 9781450334730 1450334733 |
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| DOI: | 10.1145/2740908.2742731 |