Book Volume 9994 2016

Information Retrieval Technology

12th Asia Information Retrieval Societies Conference, AIRS 2016, Beijing, China, November 30 – December 2, 2016, Proceedings

ISBN: 978-3-319-48050-3 (Print) 978-3-319-48051-0 (Online)

Table of contents (32 chapters)

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  1. Front Matter

    Pages I-XIII

  2. IR Models and Theories

    1. Front Matter

      Pages 1-1

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      Chapter

      Pages 3-15

      Modeling Relevance as a Function of Retrieval Rank

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      Chapter

      Pages 16-28

      The Effect of Score Standardisation on Topic Set Size Design

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      Chapter

      Pages 29-41

      Incorporating Semantic Knowledge into Latent Matching Model in Search

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      Chapter

      Pages 42-55

      Keyqueries for Clustering and Labeling

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      Chapter

      Pages 56-67

      A Comparative Study of Answer-Contained Snippets and Traditional Snippets

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      Chapter

      Pages 68-80

      Local Community Detection via Edge Weighting

  3. Machine Learning and Data Mining for IR

    1. Front Matter

      Pages 81-81

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      Chapter

      Pages 83-97

      Learning a Semantic Space of Web Search via Session Data

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      Chapter

      Pages 98-110

      TLINE: Scalable Transductive Network Embedding

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      Chapter

      Pages 111-122

      Detecting Synonymous Predicates from Online Encyclopedia with Rich Features

  4. IR Applications and User Modeling

    1. Front Matter

      Pages 123-123

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      Chapter

      Pages 125-137

      Patent Retrieval Based on Multiple Information Resources

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      Chapter

      Pages 138-154

      Simulating Ideal and Average Users

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      Chapter

      Pages 155-167

      Constraining Word Embeddings by Prior Knowledge – Application to Medical Information Retrieval

  5. Personalization and Recommendation

    1. Front Matter

      Pages 169-169

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      Chapter

      Pages 171-183

      Use of Microblog Behavior Data in a Language Modeling Framework to Enhance Web Search Personalization

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      Chapter

      Pages 184-196

      A Joint Framework for Collaborative Filtering and Metric Learning

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      Chapter

      Pages 197-211

      Scrutinizing Mobile App Recommendation: Identifying Important App-Related Indicators

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      Chapter

      Pages 212-223

      User Model Enrichment for Venue Recommendation

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      Chapter

      Pages 224-236

      Learning Distributed Representations for Recommender Systems with a Network Embedding Approach

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      Chapter

      Pages 237-248

      Factorizing Sequential and Historical Purchase Data for Basket Recommendation

  6. IR Evaluation

    1. Front Matter

      Pages 249-249

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      Chapter

      Pages 251-266

      Search Success Evaluation with Translation Model

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      Chapter

      Pages 267-278

      Evaluating the Social Acceptability of Voice Based Smartwatch Search

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