Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
Modification biterm topic model input feature for detecting topic in thematic virtual museums. / Anggai, S.; Blekanov, I. S.; Sergeev, S. L.
в: Vestnik Sankt-Peterburgskogo Universiteta, Prikladnaya Matematika, Informatika, Protsessy Upravleniya, Том 14, № 3, 01.01.2018, стр. 243-251.Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
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TY - JOUR
T1 - Modification biterm topic model input feature for detecting topic in thematic virtual museums
AU - Anggai, S.
AU - Blekanov, I. S.
AU - Sergeev, S. L.
N1 - Anggai S., Blekanov I. S., Sergeev S. L. Modification biterm topic model input feature for detecting topic in thematic virtual museums. Vestnik of Saint Petersburg University. Applied Mathematics. Computer Science. Control Processes, 2018, vol. 14, iss. 3, pp. 243–251. https://doi.org/10.21638/11702/spbu10.2018.305
PY - 2018/1/1
Y1 - 2018/1/1
N2 - 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.
AB - 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.
KW - Biterm
KW - BTM
KW - Clustering
KW - Short text
KW - Thematic virtual museums
KW - Topic model
KW - тематическая модель
KW - битерм
KW - короткие тексты
KW - модель BTM
KW - кластеризация
KW - тематический виртуальный музей
UR - http://www.scopus.com/inward/record.url?scp=85056705210&partnerID=8YFLogxK
U2 - 10.21638/11702/spbu10.2018.305
DO - 10.21638/11702/spbu10.2018.305
M3 - Article
AN - SCOPUS:85056705210
VL - 14
SP - 243
EP - 251
JO - ВЕСТНИК САНКТ-ПЕТЕРБУРГСКОГО УНИВЕРСИТЕТА. ПРИКЛАДНАЯ МАТЕМАТИКА. ИНФОРМАТИКА. ПРОЦЕССЫ УПРАВЛЕНИЯ
JF - ВЕСТНИК САНКТ-ПЕТЕРБУРГСКОГО УНИВЕРСИТЕТА. ПРИКЛАДНАЯ МАТЕМАТИКА. ИНФОРМАТИКА. ПРОЦЕССЫ УПРАВЛЕНИЯ
SN - 1811-9905
IS - 3
ER -
ID: 36273770