Building the Semantic Similarity Model for Social Network Data Streams
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.