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Special Interest Group on Information Retrieval Conference (2020)


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    Proceedings of the First Workshop on Bridging the Gap between Information Science, Information Retrieval and Data Science (BIRDS 2020) co-located with 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2020), Xi'an, China (online only), July 30th, - 2020

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    Proceedings of the First Workshop on Bridging the Gap between Information Science, Information Retrieval and Data Science (BIRDS 2020) co-located with 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2020), Xi'an, China (online only), July 30th, - 2020

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    BIRDS 2020 - Bridging the Gap between Information Science, Information Retrieval and Data Science: Preface

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    Fairness and Transparency in Ranking
    Carlos Castillo

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    Challenges and Opportunities for IS, IR & DS in an Era of Information Ubiquity
    Nicholas J. Belkin

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    Explaining Explanation Methods
    Riccardo Guidotti

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    Understanding Faceted Search from Information Retrieval, Information Science and Data Science Perspectives
    Xi Niu

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    Reinforcement Learning-driven Information Seeking: A Quantum Probabilistic Approach
    Amit Kumar Jaiswal | Haiming Liu | Ingo Frommholz

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    Towards a Framework for Harm Prevention in Web Search
    Steven Zimmerman | Stefan Herzog | Jon Chamberlain | David Elsweiler | Udo Kruschwitz

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    Temporal Analysis of Scientific Literature to Find Grand Challenges and Saturated Problems
    Kritika Agrawal | Vikram Pudi

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    Exploring the Impact on User Information Search Behaviour of Affective Design: An Eye-Tracking Study
    Sehrish Sher Khan | Haiming Liu

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    Extracting and Representing Causal Knowledge of Health Condition
    Hong Qing Yu

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    BM25-FIC: Information Content-based Field Weighting for BM25F
    Tuomas Ketola | Thomas Roelleke

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    Content-based Image Search System Design for Capturing User Preferences during Query Formulation
    Mahmoud Artemi | Haiming Liu

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    Some Reflections on the Use of Structural Equation Modeling for Investigating the Causal Relationships that Affect Search Engine Results
    Massimo Melucci