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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Shaoze Lei JianWen Zhang Shifeng Weng Changshui Zhang |
| Copyright Year | 2011 |
| Description | Author affiliation: State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology(TNList), Department of Automation Engineering, Tsinghua University, Beijing 100084, China (Shaoze Lei; JianWen Zhang; Changshui Zhang) || School of Electronics and Information, Zhejiang Wanli University, 315100, China (Shifeng Weng) |
| Abstract | Word burstiness phenomenon, which means that if a word occurs once in a document it is likely to occur repeatedly, has interested the text analysis field recently. Dirichlet Compound Multinomial Latent Dirichlet Allocation (DCMLDA) introduces this word burstiness mechanism into Latent Dirichlet Allocation (LDA). However, in DCMLDA, there is no restriction on the word burstiness intensity of each topic. Consequently, as shown in this paper, the burstiness intensities of words in major topics will become extremely low and the topics' ability to represent different semantic meanings will be impaired. In order to get topics that represent semantic meanings of documents well, we introduce constraints on topics' word burstiness intensities. Experiments demonstrate that DCMLDA with constrained word burstiness intensities achieves better performance than the original one without constraints. Besides, these additional constraints help to reveal the relationship between two key properties inherited from DCM and LDA respectively. These two properties have a great influence on the combined model's performance and their relationship revealed by this paper is an important guidance for further study of topic models. |
| Starting Page | 68 |
| Ending Page | 74 |
| File Size | 680498 |
| Page Count | 7 |
| File Format | |
| ISBN | 9781424496358 |
| ISSN | 21614407 |
| e-ISBN | 9781424496372 |
| DOI | 10.1109/IJCNN.2011.6033201 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-07-31 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Semantics Optimization Monte Carlo methods Resource management Compounds Inference algorithms Educational institutions |
| Content Type | Text |
| Resource Type | Article |
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