research-article

Integrating Representation and Interaction for Context-Aware Document Ranking

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Ji-Rong WenAuthors Info & Claims

ACM Transactions on Information Systems, Volume 41, Issue 1

Article No.: 21, Pages 1 - 23

https://doi.org/10.1145/3529955

Published: 10 January 2023 Publication History

Abstract

Recent studies show that historical behaviors (such as queries and their clicks) contained in a search session can benefit the ranking performance of subsequent queries in the session. Existing neural context-aware ranking models usually rank documents based on either latent representations of user search behaviors or the word-level interactions between the candidate document and each historical behavior in the search session. However, these two kinds of models both have their own drawbacks. Representation-based models neglect fine-grained information on word-level interactions, whereas interaction-based models suffer from the length restriction of session sequence because of the large cost of word-level interactions. To complement the limitations of these two kinds of models, we propose a unified context-aware document ranking model that takes full advantage of both representation and interaction. Specifically, instead of matching a candidate document with every single historical query in a session, we encode the session history into a latent representation and use this representation to enhance the current query and the candidate document. We then just match the enhanced query and candidate document with several matching components to capture the fine-grained information of word-level interactions. Rich experiments on two public query logs prove the effectiveness and efficiency of our model for leveraging representation and interaction.

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Index Terms

Integrating Representation and Interaction for Context-Aware Document Ranking
1. Information systems
  1. Information retrieval
    1. Retrieval models and ranking

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cover image ACM Transactions on Information Systems

ACM Transactions on Information Systems Volume 41, Issue 1

January 2023

759 pages

ISSN:1046-8188

EISSN:1558-2868

DOI:10.1145/3570137

Editor:
Min Zhang
Tsinghua University, China

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Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 10 January 2023

Online AM: 14 April 2022

Accepted: 30 March 2022

Revised: 22 February 2022

Received: 10 September 2021

Published in TOIS Volume 41, Issue 1

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National Natural Science Foundation of China
Beijing Outstanding Young Scientist Program
Intelligent Social Governance Platform, Major Innovation & Planning Interdisciplinary Platform for the “Double-First Class” Initiative, Renmin University of China

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https://dl.acm.org/doi/10.1145/3664928
Shahbazi NSintos SAsudeh A(2024)FairHash: A Fair and Memory/Time-efficient HashmapProceedings of the ACM on Management of Data10.1145/36549392:3(1-29)Online publication date: 30-May-2024
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