Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Anton Thielmann"'
Autor:
Christoph Weisser, Christoph Gerloff, Anton Thielmann, Andre Python, Arik Reuter, Thomas Kneib, Benjamin Säfken
Publikováno v:
Computational Statistics. 38:647-674
Topic models are a useful and popular method to find latent topics of documents. However, the short and sparse texts in social media micro-blogs such as Twitter are challenging for the most commonly used Latent Dirichlet Allocation (LDA) topic model.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bd0649f062a56bc8388b122b216dd03d
https://doi.org/10.1007/s00180-022-01246-z
https://doi.org/10.1007/s00180-022-01246-z
Publikováno v:
2023 IEEE 17th International Conference on Semantic Computing (ICSC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d8a1ed6e1fed67f109f3a8c6aaf94230
https://doi.org/10.1109/icsc56153.2023.00009
https://doi.org/10.1109/icsc56153.2023.00009
Autor:
Quentin Edward Seifert, Anton Thielmann, Elisabeth Bergherr, Benjamin Säfken, Jakob Zierk, Manfred Rauh, Tobias Hepp
Mixture Density Networks (MDN) belong to a class of models that can be applied to data which cannot be sufficiently described by a single distribution since it originates from different components of the main unit and therefore needs to be described
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bddae33f3cf84494035cd35a12d33f21
https://doi.org/10.21203/rs.3.rs-2398185/v1
https://doi.org/10.21203/rs.3.rs-2398185/v1
Publikováno v:
Soft Computing: Biomedical and Related Applications ISBN: 9783030766191
The present contribution suggests a two-step classification rule for unsupervised document classification, using one-class Support Vector Machines and Latent Dirichlet Allocation Topic Modeling. The integration of both algorithms allows the usage of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f26c014199065d92df1b1d3636663cba
https://doi.org/10.1007/978-3-030-76620-7_23
https://doi.org/10.1007/978-3-030-76620-7_23
Unsupervised document classification integrating web scraping, one-class SVM and LDA topic modelling
Publikováno v:
J Appl Stat
Unsupervised document classification for imbalanced data sets poses a major challenge. To obtain accurate classification results, training data sets are often created manually by humans which requires expert knowledge, time and money. Depending on th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9db6d46826812971e39eca80f2fcc87c
Autor:
Christoph Weisser, Arne Tillmann, Benjamin Säfken, Alexander Silbersdorff, Thomas Kneib, Anton Thielmann, Gillian Kant
Publikováno v:
Journal of Open Source Software. 6:3719
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a1c8cad5b20c8a80c297aa3ba20c270b
https://doi.org/10.21105/joss.03719
https://doi.org/10.21105/joss.03719