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Inferring and using location metadata to personalize web search

Authors:

Paul N. Bennett,

Filip Radlinski,

Emine YilmazAuthors Info & Claims

SIGIR '11: Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval

Pages 135 - 144

https://doi.org/10.1145/2009916.2009938

Published: 24 July 2011 Publication History

Abstract

Personalization of search results offers the potential for significant improvements in Web search. Among the many observable user attributes, approximate user location is particularly simple for search engines to obtain and allows personalization even for a first-time Web search user. However, acting on user location information is difficult, since few Web documents include an address that can be interpreted as constraining the locations where the document is relevant. Furthermore, many Web documents -- such as local news stories, lottery results, and sports team fan pages -- may not correspond to physical addresses, but the location of the user still plays an important role in document relevance. In this paper, we show how to infer a more general location relevance which uses not only physical location but a more general notion of locations of interest for Web pages. We compute this information using implicit user behavioral data, characterize the most location-centric pages, and show how location information can be incorporated into Web search ranking. Our results show that a substantial fraction of Web search queries can be significantly improved by incorporating location-based features.

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Cited By

Bai YZhou YDou ZWen J(2024)Intent-Oriented Dynamic Interest Modeling for Personalized Web SearchACM Transactions on Information Systems10.1145/363981742:4(1-30)Online publication date: 8-Jan-2024
https://dl.acm.org/doi/10.1145/3639817
Meng YLi RQin HWu XDuan HLu YWang G(2024)Encoding Group Interests With Persistent Homology for Personalized SearchIEEE Transactions on Systems, Man, and Cybernetics: Systems10.1109/TSMC.2024.341002954:9(5606-5616)Online publication date: Sep-2024
https://doi.org/10.1109/TSMC.2024.3410029
Wang SDou ZYao JZhou YWen J(2023)Incorporating Explicit Subtopics in Personalized SearchProceedings of the ACM Web Conference 202310.1145/3543507.3583488(3364-3374)Online publication date: 30-Apr-2023
https://dl.acm.org/doi/10.1145/3543507.3583488
Show More Cited By

Index Terms

Inferring and using location metadata to personalize web search
1. Information systems
  1. Information retrieval

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Information & Contributors

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Published In

cover image ACM Conferences

SIGIR '11: Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval

July 2011

1374 pages

ISBN:9781450307574

DOI:10.1145/2009916

General Chairs:
Wei-Ying Ma
Microsoft Research Asia, China
,
Jian-Yun Nie
University of Montreal, Canada
,
Program Chairs:
Ricardo Baeza-Yates
Yahoo! Research, Spain
,
Tat-Seng Chua
National University of Singapore
,
W. Bruce Croft
University of Massachusetts, Amherst, USA

Copyright © 2011 ACM.

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 ACM 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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SIGIR: ACM Special Interest Group on Information Retrieval

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 July 2011

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SIGIR '11: The 34th International ACM SIGIR conference on research and development in Information Retrieval

July 24 - 28, 2011

Beijing, China

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Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Cited By

Bai YZhou YDou ZWen J(2024)Intent-Oriented Dynamic Interest Modeling for Personalized Web SearchACM Transactions on Information Systems10.1145/363981742:4(1-30)Online publication date: 8-Jan-2024
https://dl.acm.org/doi/10.1145/3639817
Meng YLi RQin HWu XDuan HLu YWang G(2024)Encoding Group Interests With Persistent Homology for Personalized SearchIEEE Transactions on Systems, Man, and Cybernetics: Systems10.1109/TSMC.2024.341002954:9(5606-5616)Online publication date: Sep-2024
https://doi.org/10.1109/TSMC.2024.3410029
Wang SDou ZYao JZhou YWen J(2023)Incorporating Explicit Subtopics in Personalized SearchProceedings of the ACM Web Conference 202310.1145/3543507.3583488(3364-3374)Online publication date: 30-Apr-2023
https://dl.acm.org/doi/10.1145/3543507.3583488
Wang BLiu J(2023)Characterizing and Early Predicting User Performance for Adaptive Search Path RecommendationProceedings of the Association for Information Science and Technology10.1002/pra2.79960:1(408-420)Online publication date: 22-Oct-2023
https://doi.org/10.1002/pra2.799
Qian XRossi RDu FKim SKoh EMalik SLee TAhmed N(2022)Personalized Visualization RecommendationACM Transactions on the Web10.1145/3538703Online publication date: 24-May-2022
https://doi.org/10.1145/3538703
Dan OParikh VDavison B(2022)IP Geolocation through Geographic ClicksACM Transactions on Spatial Algorithms and Systems10.1145/34767748:1(1-22)Online publication date: 4-Mar-2022
https://dl.acm.org/doi/10.1145/3476774
Hong DJung WShim K(2022)Collecting Geospatial Data Under Local Differential Privacy With Improving Frequency EstimationIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2022.3181049(1-12)Online publication date: 2022
https://doi.org/10.1109/TKDE.2022.3181049
Vannieuwenhuyze JSmets AGebert MBallon P(2022)Methodological analysis of personalization in urban recommender systems by distance measuresTelematics and Informatics10.1016/j.tele.2022.10181871:COnline publication date: 1-Jul-2022
https://dl.acm.org/doi/10.1016/j.tele.2022.101818
Shah CWhite R(2021)Task Intelligence for Search and RecommendationSynthesis Lectures on Information Concepts, Retrieval, and Services10.2200/S01103ED1V01Y202105ICR07413:3(1-160)Online publication date: 9-Jun-2021
https://doi.org/10.2200/S01103ED1V01Y202105ICR074
Yao JDou ZWen J(2021)Clarifying Ambiguous Keywords with Personal Word Embeddings for Personalized SearchACM Transactions on Information Systems10.1145/347056440:3(1-29)Online publication date: 22-Nov-2021
https://dl.acm.org/doi/10.1145/3470564
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