Name
Title | ||
|---|---|---|
Learning persona-driven personalized sentimental representation for review-based recommendation |
Abstract | ||
|---|---|---|
A large amount of information exists in many e-commerce and review websites as a valuable source for recommender systems. Recent solutions focus on exploring the correlation between sentiment and textual reviews in the review-based recommendation. However, these studies usually pay less attention to the differences of different users in sentimental expression styles or language usage habits when a user writes reviews. In this work, we argue that the individual reviewing behavior is closely related to personality, and sentimental expression is a manifestation of personality. Therefore, we propose a novel Persona-driven Sentimental Attentive Recommendation model (named PSAR) via personalized sentimental interactive representation learning for the review-based recommendation. The proposed model is devised to learn fragment-level and sequence-level personalized sentimental representation simultaneously from reviews. Besides, an attentive persona-driven interaction module is designed to capture word-level usage habits and sentence-level analogous tones. Comprehensive experimental results on four real-world datasets demonstrate that our model outperforms the state-of-the-art methods. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.eswa.2022.117317 | Expert Systems with Applications |
Keywords | DocType | Volume |
00-01,99-00 | Journal | 203 |
ISSN | Citations | PageRank |
0957-4174 | 0 | 0.34 |
References | Authors | |
29 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peipei Wang | 1 | 2 | 1.75 |
| Li Lin | 2 | 96 | 36.67 |
| Ru Wang | 3 | 0 | 0.34 |
| Xinhao Zheng | 4 | 0 | 0.34 |
| Jiaxi He | 5 | 0 | 0.34 |
| Guandong Xu | 6 | 640 | 75.03 |