Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Trong Dinh Thac Do"'
Publikováno v:
IEEE Intelligent Systems. 36:35-47
Community question answering (CQA) recommends appropriate answers to existing and new questions. Such answer recommendation is challenging since CQA data are often sparse and decentralized, and lacks sufficient information to generate suitable answer
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Autor:
Longbing Cao, Trong Dinh Thac Do
Publikováno v:
IJCAI
Matrix Factorization (MF) is widely used in Recommender Systems (RSs) for estimating missing ratings in the rating matrix. MF faces major challenges of handling very sparse and large data. Poisson Factorization (PF) as an MF variant addresses these c
Autor:
Trong Dinh Thac Do, Longbing Cao
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 32
Modelling sparse and large data sets is highly in demand yet challenging in recommender systems. With the computation only on the non-zero ratings, Poisson Factorization (PF) enabled by variational inference has shown its high efficiency in scalable
Autor:
Trong Dinh Thac Do, Behrooz Omidvar-Tehrani, Sihem Amer-Yahia, Anne Laurent, Benjamin Negrevergne, Alexandre Termier
Publikováno v:
Knowledge and Information Systems (KAIS)
Knowledge and Information Systems (KAIS), Springer, 2015, 43 (3), pp.497-527. ⟨10.1007/s10115-014-0749-8⟩
Knowledge and Information Systems (KAIS), 2015, 43 (3), pp.497-527. ⟨10.1007/s10115-014-0749-8⟩
Knowledge and Information Systems (KAIS), Springer, 2015, 43 (3), pp.497-527. ⟨10.1007/s10115-014-0749-8⟩
Knowledge and Information Systems (KAIS), 2015, 43 (3), pp.497-527. ⟨10.1007/s10115-014-0749-8⟩
International audience; Numerical data (e.g., DNA micro-array data, sensor data) pose a challenging problem to existing frequent pattern mining methods which hardly handle them. In this framework, gradual patterns have been recently proposed to extra
Publikováno v:
International Conference on Data Mining
ICDM: International Conference on Data Mining
ICDM: International Conference on Data Mining, Dec 2010, Sidney, NSW, Australia. pp.138-147, ⟨10.1109/ICDM.2010.101⟩
ICDM
ICDM: International Conference on Data Mining
ICDM: International Conference on Data Mining, Dec 2010, Sidney, NSW, Australia. pp.138-147, ⟨10.1109/ICDM.2010.101⟩
ICDM
International audience; Numerical data (e.g., DNA micro-array data, sensor data) pose a challenging problem to existing frequent pattern mining methods which hardly handle them. In this framework, gradual patterns have been recently proposed to extra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bb126e26dcc9eb8609a0d4bf446e5809
https://hal.archives-ouvertes.fr/hal-00952985/file/hal-00952985v1.pdf
https://hal.archives-ouvertes.fr/hal-00952985/file/hal-00952985v1.pdf
Akademický článek
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Publikováno v:
2010 IEEE 10th International Conference on Data Mining (ICDM); 2010, p138-147, 10p