Unsupervised Open Relation Extraction

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2021vVol_II___Proceedings_of_the_5th_International_conference_COLINS_2021_Workshop_Kharkiv_Ukraine_April_22-23_Tarasenko_Y-Unsupervised_Open_Relation_93-94.pdf (247.72 KB)
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Date

2021-05-04

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Abstract

The paper describes an approach to open relation extraction based on unsupervised machine learning. The state-of-the-art methods for extracting semantic relations are analyzed. The algorithm of automatic open relation extraction using statistical, syntactic and contextual information is proposed. The results of the study can be used in information retrieval, summarization, machine translation, question-answering systems, etc.

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Keywords

Information Extraction, Open Relation Extraction, semantic relation, TF-IDF, parsing, cluster analysis

Citation

Tarasenko Y. Unsupervised Open Relation Extraction / Yaroslav Tarasenko, Svitlana Petrasova // Computational linguistics and intelligent systems, 22-23 April 2021, Kharkiv. — Lviv ; Kharkiv, 2021. — Vol Vol. II : Proceedings of the 5th International conference, COLINS 2021, Workshop, Kharkiv, Ukraine, April 22-23. — P. 93–94.

URI

https://ena.lpnu.ua/handle/ntb/56806

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Computational linguistics and intelligent systems. – 2021 р.