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Recommending topics in dialogue.
- Source :
-
World Wide Web . Sep2018, Vol. 21 Issue 5, p1165-1185. 21p. - Publication Year :
- 2018
-
Abstract
- Several types of online chat system have been developed; however, there exist no recommendation systems for the recommendation of topics suitable for discussion with a given individual at a particular time. This paper proposes a hot-topic recommendation system based on analysis of the tweets posted by the user, his/her chat partners, and similar users of his/her chat partners, as well as hashtags trending in Twitter. In experiments, the proposed system, which is based on the well-known Latent Dirichlet Allocation (LDA) algorithm, was shown to outperform existing recommendation systems with regard to computational efficiency as well as prediction accuracy. [ABSTRACT FROM AUTHOR]
- Subjects :
- *ONLINE chat
*DIALOGUE
*RECOMMENDER systems
*TAGS (Metadata)
Subjects
Details
- Language :
- English
- ISSN :
- 1386145X
- Volume :
- 21
- Issue :
- 5
- Database :
- Academic Search Index
- Journal :
- World Wide Web
- Publication Type :
- Academic Journal
- Accession number :
- 131336272
- Full Text :
- https://doi.org/10.1007/s11280-017-0499-0