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Web Document Encoding for Structure-Aware Keyphrase Extraction
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Kim, Jihyuk | - |
| dc.contributor.author | Song, Young-In | - |
| dc.contributor.author | Seung-Won, Hwang | - |
| dc.date.accessioned | 2022-06-24T00:25:52Z | - |
| dc.date.available | 2022-06-24T00:25:52Z | - |
| dc.date.created | 2022-05-09 | - |
| dc.date.issued | 2021-07 | - |
| dc.identifier.citation | SIGIR 2021 - Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp.1823-1827 | - |
| dc.identifier.uri | https://hdl.handle.net/10371/183734 | - |
| dc.description.abstract | © 2021 ACM.We study keyphrase extraction (KPE) from Web documents. Our key contribution is encoding Web documents to leverage structure, such as title or anchors, by building a graph of words representing both (a) position-based proximity and (b) structural relations. We evaluate KPE performance on real-world search engine NAVER and human-annotated KPE benchmarks, and ours outperforms state-of-the-arts in both tasks. | - |
| dc.language | 영어 | - |
| dc.publisher | Association for Computing Machinery, Inc | - |
| dc.title | Web Document Encoding for Structure-Aware Keyphrase Extraction | - |
| dc.type | Article | - |
| dc.identifier.doi | 10.1145/3404835.3463067 | - |
| dc.citation.journaltitle | SIGIR 2021 - Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval | - |
| dc.identifier.wosid | 000719807900202 | - |
| dc.identifier.scopusid | 2-s2.0-85111696686 | - |
| dc.citation.endpage | 1827 | - |
| dc.citation.startpage | 1823 | - |
| dc.description.isOpenAccess | N | - |
| dc.contributor.affiliatedAuthor | Seung-Won, Hwang | - |
| dc.type.docType | Conference Paper | - |
| dc.description.journalClass | 1 | - |
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