Fayoumi, Kenan and Yeniterzi, Reyyan (2019) OzU-NLP at TREC NEWS 2019: entity ranking. In: 28th Text REtrieval Conference (TREC), Gaithersburg, MD, USA
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Official URL: https://trec.nist.gov/pubs/trec28/papers/OzUNLP.News.pdf
Abstract
This paper presents our work and submission for TREC 2019 News
Track: Entity Ranking Task. Our approach utilizes Doc2Vec’s ability
to represent documents as fixed sized numerical vectors. Applied on
news articles and wiki-pages of the entities, Doc2Vec provides us with
vector representations for these two that we can utilize to perform
ranking on entities. We also investigate whether background linked
articles can be useful for entity ranking task.
| Item Type: | Papers in Conference Proceedings |
|---|---|
| Divisions: | Faculty of Engineering and Natural Sciences > Academic programs > Computer Science & Eng. Faculty of Engineering and Natural Sciences |
| Depositing User: | Reyyan Yeniterzi |
| Date Deposited: | 19 Sep 2020 07:56 |
| Last Modified: | 11 Jun 2024 09:51 |
| URI: | https://research.sabanciuniv.edu/id/eprint/40333 |
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