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9 Result(s)
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Shu-wu **e
Information Storage and Retrieval
Information Systems Applications (incl. Internet)
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Book
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Chapter
Context-Aware Recurrent Structure
To investigate and address the problem of context-aware sequential prediction, this chapter introduces a sequential prediction model, named context-aware recurrent neural networks (CA-RNNs). Instead of using t...
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Chapter
Context-Aware Collaborative Prediction
Context-aware collaborative prediction takes contextual information into consideration when modeling user preferences and predicting user behaviors. There are two general ways to integrate contexts with collab...
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Chapter
Hierarchical Representation
This chapter introduces a hierarchical interaction representation (HIR) model, which treats the interaction among different entities and contexts as representation. This model generates the interaction represe...
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Chapter
Introduction
In this chapter, we introduce the basic concepts of contextual information and collaborative prediction. Then, we introduce the scenarios of context-aware collaborative prediction and point out some limitation...
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Chapter
Contextual Operation
Motivated by recent works of natural language processing, this chapter introduces the concept of contextual operation for context-aware modeling. This operation represents each context value with a latent vect...
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Chapter
Performance of Different Collaborative Prediction Tasks
This chapter contains the experiments of four tasks, i.e., general recommendation, context-aware recommendation, latent collaborative retrieval, and click-through rate prediction. At first, this chapter descri...
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Chapter and Conference Paper
Multiple Attribute Aware Personalized Ranking
Personalized ranking is a typical task of recommender systems. It can provide a set of items for specific user and help recommender systems more correctly direct each item to its user. Recently, as the dramati...
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Chapter and Conference Paper
Learning to Hash for Recommendation with Tensor Data
Recommender systems usually need to compare user interests and item characteristics in the context of large user and item space, making hashing based algorithms a promising strategy to speed up recommendation....
