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

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Modification biterm topic model input feature for detecting topic in thematic virtual museums. / Anggai, S.; Blekanov, I. S.; Sergeev, S. L.

In: Vestnik Sankt-Peterburgskogo Universiteta, Prikladnaya Matematika, Informatika, Protsessy Upravleniya, Vol. 14, No. 3, 01.01.2018, p. 243-251.

Research output: Contribution to journal › Article › peer-review

Author

Anggai, S. ; Blekanov, I. S. ; Sergeev, S. L. / Modification biterm topic model input feature for detecting topic in thematic virtual museums. In: Vestnik Sankt-Peterburgskogo Universiteta, Prikladnaya Matematika, Informatika, Protsessy Upravleniya. 2018 ; Vol. 14, No. 3. pp. 243-251.

BibTeX

@article{669c502d9081439eb1d0f88ab657ecc1,

title = "Modification biterm topic model input feature for detecting topic in thematic virtual museums",

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 = "Biterm, BTM, Clustering, Short text, Thematic virtual museums, Topic model, тематическая модель, битерм, короткие тексты, модель BTM, кластеризация, тематический виртуальный музей",

author = "S. Anggai and Blekanov, {I. S.} and Sergeev, {S. L.}",

note = "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",

year = "2018",

month = jan,

day = "1",

doi = "10.21638/11702/spbu10.2018.305",

language = "English",

volume = "14",

pages = "243--251",

journal = " ВЕСТНИК САНКТ-ПЕТЕРБУРГСКОГО УНИВЕРСИТЕТА. ПРИКЛАДНАЯ МАТЕМАТИКА. ИНФОРМАТИКА. ПРОЦЕССЫ УПРАВЛЕНИЯ",

issn = "1811-9905",

publisher = "Издательство Санкт-Петербургского университета",

number = "3",

}

RIS

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