CASIA OpenIR  > 智能感知与计算研究中心
Collaborative Prediction for Multi-entity Interaction With Hierarchical Representation
Liu, Qiang; Wu, Shu; Wang, Liang
2015
Conference NameACM International Conference on Information and Knowledge Management (CIKM)
Source PublicationIn Proceedings of the 24th ACM International Conference on Information and Knowledge Management (CIKM), 2015
Conference DateOct 24-28
Conference PlaceMelbourne
AbstractWith 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).
KeywordCollaborative Prediction Factorization Model Hierarchical Representation
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12338
Collection智能感知与计算研究中心
Corresponding AuthorWu, Shu
AffiliationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Liu, Qiang,Wu, Shu,Wang, Liang. Collaborative Prediction for Multi-entity Interaction With Hierarchical Representation[C],2015.
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