| Collaborative Prediction for Multi-entity Interaction With Hierarchical Representation | |
Liu, Qiang ; Wu, Shu; Wang, Liang
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| 2015 | |
| 会议名称 | ACM International Conference on Information and Knowledge Management (CIKM) |
| 会议录名称 | In Proceedings of the 24th ACM International Conference on Information and Knowledge Management (CIKM), 2015 |
| 会议日期 | Oct 24-28 |
| 会议地点 | Melbourne |
| 摘要 | With the rapid growth of Internet applications, there are more and more entities in interaction scenarios, and thus collaborative prediction for multi-entity interaction is becoming a significant problem. The state-of-the-art methods, e.g., tensor factorization and factorization machine, predict multi-entity interaction based on calculating the similarity among all entities. However, these methods are usually not able to reveal the joint characteristics of entities in the interaction. Besides, some methods may succeed in one specific application, but they can not be extended effectively for other applications or interaction scenarios with more entities. In this work, we propose a Hierarchical Interaction Representation (HIR) model, which models the mutual action among different entities as a joint representation. We generate the interaction representation of two entities via tensor multiplication, which is preformed iteratively to construct a hierarchical structure among all entities. Moreover, we employ several hidden layers to reveal the underlying properties of this interaction and enhance the model performance. After generating final representation, the prediction can be calculated using a variety of machine learning methods according to different tasks (i.e., linear regression for regression tasks, pair-wise ranking for ranking tasks and logistic regression for classification tasks). Experimental results show that our proposed HIR model yields significant improvements over the competitive compared methods in four different application scenarios (i.e., general recommendation, context-aware recommendation, latent collaborative retrieval and click-through rate prediction). |
| 关键词 | Collaborative Prediction Factorization Model Hierarchical Representation |
| 文献类型 | 会议论文 |
| 条目标识符 | http://ir.ia.ac.cn/handle/173211/12338 |
| 专题 | 智能感知与计算研究中心 |
| 通讯作者 | Wu, Shu |
| 作者单位 | Institute of Automation, Chinese Academy of Sciences |
| 第一作者单位 | 中国科学院自动化研究所 |
| 通讯作者单位 | 中国科学院自动化研究所 |
| 推荐引用方式 GB/T 7714 | Liu, Qiang,Wu, Shu,Wang, Liang. Collaborative Prediction for Multi-entity Interaction With Hierarchical Representation[C],2015. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| Collaborative Predic（1709KB） | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 | ||
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