Term based semantic clusters for very short text classification

Autor: Paalman, Jasper, Mullick, Shantanu, Zervanou, Kalliopi, Zhang, Yingqian, Angelova, Galia, Mitkov, Ruslan, Nikolova, Ivelina, Temnikova, Irina

Publikováno v: 31st Benelux Conference on Artificial Intelligence and 28th Belgian-Dutch Conference on Machine Learning, BNAIC/BeneLearn 2019
International Conference on Recent Advances in Natural Language Processing in a Deep Learning World, RANLP 2019-Proceedings, 878-887
STARTPAGE=878;ENDPAGE=887;TITLE=International Conference on Recent Advances in Natural Language Processing in a Deep Learning World, RANLP 2019-Proceedings
Pure TUe
RANLP
Scopus-Elsevier

Very short texts, such as tweets and invoices, present challenges in classification. Although term occurrences are strong indicators of content, in very short texts, the sparsity of these texts makes it difficult to capture important semantic relatio

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c1a78767f98d5758e74334d8d7cc7653
https://research.tue.nl/nl/publications/6ce69081-5e7a-4d26-b266-a90b9ac95b58