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JOURNALS // Vestnik Sankt-Peterburgskogo Universiteta. Seriya 10. Prikladnaya Matematika. Informatika. Protsessy Upravleniya // Archive

Vestnik S.-Petersburg Univ. Ser. 10. Prikl. Mat. Inform. Prots. Upr., 2018 Volume 14, Issue 3, Pages 243–251 (Mi vspui373)

Computer science

Modification biterm topic model input feature for detecting topic in thematic virtual museums

S. Anggaia, I. S. Blekanov, S. L. Sergeev

a St. Petersburg State University, 7–9, Universitetskaya nab., St. Petersburg, 199034, Russian Federation

Abstract: This paper describes the method for detecting topic in short text documents developed by the authors. The method called Feature BTM, based on the modification of the third step of the generative process of the well-known BTM model. The authors conducted experiments of quality evaluation that have shown the advantage of efficiency by the modified Feature BTM model before the Standard BTM model. The thematic clustering technology of documents necessary for the creation of thematic virtual museums has described. The authors performed a performance evaluation that shows a slight loss of speed (less than 30 seconds), more effective using the Feature-BTM for clustering the virtual museum collection than the Standard BTM model.

Keywords: topic model, biterm, short text, BTM, clustering, thematic virtual museums.

UDC: 025.4.03:[004.4:351.852]

MSC: 68T50

Received: March 10, 2018
Accepted: June 14, 2018

Language: English

DOI: 10.21638/11701/spbu10.2018.305



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