Relevance segmentation of long documents
In this paper, we present our methods to identify the most salient topics for a selected domain based on topic modeling. We propose a topic relevance score and segmentation procedure which can split the document into parts referring to various topics. We also offer a solution for visualizing textual...
Elmentve itt :
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| Testületi szerző: | |
| Dokumentumtípus: | Könyv része |
| Megjelent: |
2018
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| Sorozat: | Magyar Számítógépes Nyelvészeti Konferencia
14 |
| Kulcsszavak: | Nyelvészet - számítógép alkalmazása |
| Online Access: | http://acta.bibl.u-szeged.hu/59063 |
| Tartalmi kivonat: | In this paper, we present our methods to identify the most salient topics for a selected domain based on topic modeling. We propose a topic relevance score and segmentation procedure which can split the document into parts referring to various topics. We also offer a solution for visualizing textual spans that are related to a given topic. In this way, it can be easily determined which are the most relevant and most irrelevant segments of a long document (like blog posts or news articles). |
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| Terjedelem/Fizikai jellemzők: | 405-412 |
| ISBN: | 978-963-306-578-5 |