Building the Semantic Similarity Model for Social Network Data Streams

Ескіз

Дата

2018

ORCID

DOI

doi.org/10.1109/DSMP.2018.8478480

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Назва журналу

Номер ISSN

Назва тому

Видавець

Institute of Electrical and Electronics Engineers

Анотація

This paper proposes the model for searching similar collocations in English texts in order to determine semantically connected text fragments for social network data streams analysis. The logical-linguistic model uses semantic and grammatical features of words to obtain a sequence of semantically related to each other text fragments from different actors of a social network. In order to implement the model, we leverage Universal Dependencies parser and Natural Language Toolkit with the lexical database WordNet. Based on the Blog Authorship Corpus, the experiment achieves over 0.92 precision.

Опис

Ключові слова

social network, data stream, collocations, semantic similarity, blogs, corpus, Universal Dependencies, WordNet

Бібліографічний опис

Petrasova S. Building the Semantic Similarity Model for Social Network Data Streams / S. Petrasova, N. Khairova, W. Lewoniewski // 2018 IEEE Second International Conference on Data Stream Mining & Processing (DSMP), 21-25 August 2018, Lviv, Ukraine : bk. of abstr. – Lviv : IEEE, 2018. – P. 21-24.

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