Unsupervised Open Relation Extraction
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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.
Description
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.