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Learning to rank search results for time-sensitive queries

Published: 29 October 2012 Publication History

Abstract

Retrieval effectiveness of temporal queries can be improved by taking into account the time dimension. Existing temporal ranking models follow one of two main approaches: 1) a mixture model linearly combining textual similarity and temporal similarity, and 2) a probabilistic model generating a query from the textual and temporal part of document independently. In this paper, we propose a novel time-aware ranking model based on learning-to-rank techniques. We employ two classes of features for learning a ranking model, entity-based and temporal features, which are derived from annotation data. Entity-based features are aimed at capturing the semantic similarity between a query and a document, whereas temporal features measure the temporal similarity. Through extensive experiments we show that our ranking model significantly improves the retrieval effectiveness over existing time-aware ranking models.

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    cover image ACM Conferences
    CIKM '12: Proceedings of the 21st ACM international conference on Information and knowledge management
    October 2012
    2840 pages
    ISBN:9781450311564
    DOI:10.1145/2396761
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    Published: 29 October 2012

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    Author Tags

    1. temporal queries
    2. time-aware ranking models

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    • (2023)Improving Product Search with Season-Aware Query-Product Semantic SimilarityCompanion Proceedings of the ACM Web Conference 202310.1145/3543873.3587625(864-868)Online publication date: 30-Apr-2023
    • (2022)Ranking Models for the Temporal Dimension of TextACM Transactions on Information Systems10.1145/356548141:2(1-34)Online publication date: 21-Dec-2022
    • (2021)Seasonal Relevance in E-Commerce SearchProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3481951(4293-4301)Online publication date: 26-Oct-2021
    • (2019)Modeling Temporal Evidence from External CollectionsProceedings of the Twelfth ACM International Conference on Web Search and Data Mining10.1145/3289600.3290966(159-167)Online publication date: 30-Jan-2019
    • (2018)Ranking Archived Documents for Structured Queries on Semantic LayersProceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries10.1145/3197026.3197049(155-164)Online publication date: 23-May-2018
    • (2018)Understanding the use of Temporal Expressions on Persian Web SearchCompanion Proceedings of the The Web Conference 201810.1145/3184558.3191635(1743-1748)Online publication date: 23-Apr-2018
    • (2018)Section-Based Focus Time Estimation of News ArticlesIEEE Access10.1109/ACCESS.2018.28829886(75452-75460)Online publication date: 2018
    • (2017)Quantification of time in Digital LibrariesProceedings of the 21st International Database Engineering & Applications Symposium10.1145/3105831.3105866(143-152)Online publication date: 12-Jul-2017
    • (2017)TiwikiProceedings of the 26th International Conference on World Wide Web Companion10.1145/3041021.3051112(1595-1600)Online publication date: 3-Apr-2017
    • (2017)Investigating Users' Time Perception during Web SearchProceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval10.1145/3020165.3020184(127-136)Online publication date: 7-Mar-2017
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