碩士 / 國立臺灣科技大學 / 資訊管理系 / 106 / This paper proposes a hybrid model of aspect-oriented sentiment prediction which integrates tensor factorization (TF) and sentiment utility logistic model (SULM). First, using sentiment dictionary words as seeds, the aspect or opinion words can be extended iteratively through double propagation. Accordingly, the users’ reviews could be represented as the features in user-item-aspect space, in which prediction model could be built. Various combinations of the hybrid model were proposed and evaluated on the Chinese reviews on places of interest at Taiwan Yilan from TripAdvisor. Experimental results show that the hybrid model can achieve better prediction performance than TF or SULM. The hybrid model also outperforms either TF or SULM while handling new user’s cold-start problem.
| Identifer | oai:union.ndltd.org:TW/106NTUS5396082 |
| Date | January 2018 |
| Creators | CHENG-ZHI HAN, 韓承志 |
| Contributors | Bor-shen Lin, 林伯慎 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 58 |
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