OzU-NLP at TREC NEWS 2019: entity ranking

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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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: 26 Apr 2022 09:36
URI: https://research.sabanciuniv.edu/id/eprint/40333

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