Abstract
As an important medium used to describe events, the short text is effective to convey emotions and communicate affective states. In this paper, we proposed a classification method based on probabilistic topic model, which greatly improve the performance of sentimental categorization methods on short text. To solve the problems of sparsity and context-dependency, we extract hidden topics behind the text and associate different words by the same topic. Evaluation on sentiment detection of short text verified the effectiveness of the proposed method.
Original language | English |
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Title of host publication | Database Systems for Advanced Applications - DASFAA 2015 International Workshops, SeCoP, BDMS, and Posters, Revised Selected Papers |
Editors | Yoshiharu ISHIKAWA, Sarana NUTANONG, An LIU, Tieyun QIAN, Muhammad Aamir CHEEMA |
Place of Publication | Switzerland |
Publisher | Springer, Cham |
Pages | 76-85 |
Number of pages | 10 |
Volume | 9052 |
ISBN (Electronic) | 9783319223247 |
ISBN (Print) | 9783319223230 |
DOIs | |
Publication status | Published - 2015 |
Externally published | Yes |
Event | The 20th International Conference on Database Systems for Advanced Applications - Hanoi, Viet Nam Duration: 20 Apr 2015 → 23 Apr 2015 http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=40103©ownerid=3190 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 9052 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | The 20th International Conference on Database Systems for Advanced Applications |
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Abbreviated title | DASFAA 2015 |
Country/Territory | Viet Nam |
City | Hanoi |
Period | 20/04/15 → 23/04/15 |
Internet address |
Bibliographical note
The authors are thankful to the anonymous reviewers for their constructive comments and suggestions on an earlier version of this paper.Keywords
- Sentiment detection
- Short text classification
- Topic-based similarity