More Web Proxy on the site http://driver.im/

research-article

A large-scale study on map search logs

Authors:

Wei-Ying MaAuthors Info & Claims

ACM Transactions on the Web (TWEB), Volume 4, Issue 3

Article No.: 8, Pages 1 - 33

https://doi.org/10.1145/1806916.1806917

Published: 20 July 2010 Publication History

Abstract

Map search engines, such as Google Maps, Yahoo! Maps, and Microsoft Live Maps, allow users to explicitly specify a target geographic location, either in keywords or on the map, and to search businesses, people, and other information of that location. In this article, we report a first study on a million-entry map search log. We identify three key attributes of a map search record—the keyword query, the target location and the user location, and examine the characteristics of these three dimensions separately as well as the associations between them. Comparing our results with those previously reported on logs of general search engines and mobile search engines, including those for geographic queries, we discover the following unique features of map search: (1) People use longer queries and modify queries more frequently in a session than in general search and mobile search; People view fewer result pages per query than in general search; (2) The popular query topics in map search are different from those in general search and mobile search; (3) The target locations in a session change within 50 kilometers for almost 80% of the sessions; (4) Queries, search target locations and user locations (both at the city level) all follow the power law distribution; (5) One third of queries are issued for target locations within 50 kilometers from the user locations; (6) The distribution of a query over target locations appears to follow the geographic location of the queried entity.

References

[1]

Andrade, L. and Silva, M. 2006. Relevance ranking for geographic IR. In Proceedings of the SIGIR Workshop on Geographical Information Retrieval.

[2]

Arya, S. and Mount, D. 1993. Approximate nearest neighbor queries in fixed dimensions. In Proceedings of the 4th Annual ACM-SIAM Symposium on Discrete Algorithms. SIAM, Philadelphia, PA, 271--280.

Digital Library

[3]

Blank, A. and Solomon, S. 2000. Power Laws and Cities Population. Arxiv preprint cond-mat/0003240.

[4]

Broder, A. 2002. A taxonomy of web search. ACM Sigir Forum. 36, 10.

Digital Library

[5]

Clauset, A., Shalizi, C., and Newman, M. 2007. Power-law distributions in empirical data. arxiv 706.

[6]

Cohen, J., Cohen, P., West, S., and Aiken, L. 1983. Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences. Erlbaum, Hillsdale, NJ.

[7]

Corder, G. and Foreman, D. 2009. Nonparametric Statistics for Non-Statisticians: A Step-by-step Approach. Wiley-Blackwell.

[8]

Delboni, T., Borges, K., and Laender, A. 2005. Geographic web search based on positioning expressions. In Proceedings of the Workshop on Geographic Information Retrieval. ACM, New York, 61--64.

Digital Library

[9]

Henrich, A. and Luedecke, V. 2007. Characteristics of geographic information needs. In Proceedings of the 4th ACM Workshop on Geographical Information Retrieval. ACM, New York, 1--6.

Digital Library

[10]

Jansen, B. and Spink, A. 2006. How are we searching the World Wide Web&quest; A comparison of nine search engine transaction logs. Inform. Process. Manage. 42, 1, 248--263.

Digital Library

[11]

Jansen, B., Spink, A., and Pederson, J. 2005. Trend analysis of AltaVista Web searching. J. Amer. Soc. Inform. Sci. Techn. 56, 6, 559--570.

Digital Library

[12]

Jones, R., Zhang, V. W., Rey, B., Jhala, P., and Stipp, E. 2008. Geographic intention and modification in web search. Int. J. Geograph. Inform. Sci. 22, 3, 229--246.

Digital Library

[13]

Kamvar, M. and Baluja, S. 2006. A large scale study of wireless search behavior: Google mobile search. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, New York, 701--709.

Digital Library

[14]

Lee, U., Liu, Z., and Cho, J. 2005. Automatic identification of user goals in Web search. In Proceedings of the 14th International Conference on World Wide Web. ACM, New York, 391--400.

Digital Library

[15]

MetaCarta. Geosearch news: http://geosearch.metacarta.com/.

[16]

Mitzenmacher, M. 2004. A brief history of generative models for power law and lognormal distributions. Inter, Math. 1, 2, 226--251.

[17]

Mount, D. M. and Arya, S. Aug 4, 2006. Ann—approximate nearest neighbor library. http://www.cs.umd.edu/mount/ANN/.

[18]

Nguyen, B. V. and Kan, M.-Y. 2007. Functional faceted web query analysis. In Proceedings of the WWW'07 Workshop on Query Log Analysis.

[19]

Pasley, R., Clough, P., Purves, R. S., and Twaroch, F. A. 2008. Mapping geographic coverage of the web. In Proceedings of the 16th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (GIS'08). ACM, New York, 1--9.

Digital Library

[20]

Pramudiono, I., Shintani, T., Takahashi, K., and Kitsuregawa, M. 2002. User behavior analysis of location aware search engine. In Proceedings of the 3rd International Conference on Mobile Data Management. 139--145.

Digital Library

[21]

Rose, D. and Levinson, D. 2004. Understanding user goals in web search. In Proceedings of the 13th International Conference on the World Wide Web. ACM, Press, New York, 13--19.

Digital Library

[22]

Sanderson, M. and Kohler, J. 2004. Analyzing geographic queries. In Proceedings of the SIGIR Workshop on Geographic Information Retrieval.

[23]

Santos, D. and Chaves, M. 2006. The place of place in geographical IR. In Proceedings of the 3rd Workshop on Geographic Information Retrieval (SIGIR). 6, 5--8.

[24]

Shen, D., Pan, R., Sun, J., Pan, J., Wu, K., Yin, J., and Yang, Q. 2005. Q2C&commat;UST: Our winning solution to query classification in KDDCUP 2005. ACM SIGKDD Explor. Newsl., 100--110.

Digital Library

[25]

Silverstein, C., Henzinger, M., Marais, H., and Moricz, M. 1999. Analysis of a very large Web search engine query log. SIGIR Forum 33, 1, 6--12.

Digital Library

[26]

Spink, A. and Jansen, B. 2004. Web Search: Public Searching on the Web. Springer.

Digital Library

[27]

Spink, A., Jansen, B., Wolfram, D., and Saracevic, T. 2002. From e-sex to e-commerce: Web search changes. Comput. 35, 3, 107--109.

Digital Library

[28]

Spink, A., Wolfram, D., Jansen, M., and Saracevic, T. 2001. Searching the Web: The public and their queries. J. Amer. Soci. Inform. Sci. Techn. 52, 3, 226--234.

Digital Library

[29]

Takahashi, K., Pramudiono, I., and Kitsuregawa, M. 2005. Geo-word centric association rule mining. In Proceedings of the 6th International Conference on Mobile Data Management. ACM, New York, 273--280.

Digital Library

[30]

Teitler, B., Lieberman, M., Panozzo, D., Sankaranarayanan, J., Samet, H., and Sperling, J. 2008. NewsStand: A new view on news. In Proceedings of the 16th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. ACM, New York.

Digital Library

[31]

van Rijsbergen, C. 1979. Information Retrieval. Butterworth.

Digital Library

[32]

Vapnik, V. 2000. The Nature of Statistical Learning Theory. Springer.

Digital Library

[33]

Wang, C., Xie, X., Wang, L., Lu, Y., and Ma, W. 2005. Detecting geographic locations from web resources. In Proceedings of the Workshop on Geographic Information Retrieval. ACM, New York, 17--24.

Digital Library

[34]

Xiao, X., Xie, X., Luo, Q., and Ma, W.-Y. 2008. Density based co-location pattern discovery. In Proceedings of the 16th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (GIS'08).

Digital Library

[35]

Yang, Y. and Pedersen, J. 1997. A comparative study on feature selection in text categorization. In Proceedings of the 14th International Conference on Machine Learning. 412--420.

Digital Library

[36]

Zhang, V., Rey, B., Stipp, E., and Jones, R. 2006. Geomodification in query rewriting. In Proceedings of the 3th ACM Workshop on Geographical Information Retrieval.

Cited By

Dong GMou XZhang HLi RWu HJiang JLi FYu W(2024)Browsing target extraction and spatiotemporal preference mining from the complex virtual trajectoriesInternational Journal of Applied Earth Observation and Geoinformation10.1016/j.jag.2024.103819129(103819)Online publication date: May-2024
https://doi.org/10.1016/j.jag.2024.103819
Dong GLi RWu HChen WHuang WZhang H(2022)Browsing behavior modeling and browsing interest extraction in the trajectories on web map service platformsExpert Systems with Applications: An International Journal10.1016/j.eswa.2022.116590195:COnline publication date: 1-Jun-2022
https://dl.acm.org/doi/10.1016/j.eswa.2022.116590
Yuan ZLiu HLiu JLiu YYang YHu RXiong H(2021)Incremental Spatio-Temporal Graph Learning for Online Query-POI MatchingProceedings of the Web Conference 202110.1145/3442381.3449810(1586-1597)Online publication date: 19-Apr-2021
https://dl.acm.org/doi/10.1145/3442381.3449810
Show More Cited By

Index Terms

A large-scale study on map search logs

Recommendations

A large scale study of wireless search behavior: Google mobile search
CHI '06: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

We present a large scale study of search patterns on Google's mobile search interface. Our goal is to understand the current state of wireless search by analyzing over 1 Million hits to Google's mobile search sites. Our study also includes the ...
Mining query subtopics from search log data
SIGIR '12: Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval

Most queries in web search are ambiguous and multifaceted. Identifying the major senses and facets of queries from search log data, referred to as query subtopic mining in this paper, is a very important issue in web search. Through search log analysis, ...
Re-ranking search results using query logs
CIKM '06: Proceedings of the 15th ACM international conference on Information and knowledge management

This work addresses two common problems in search, frequently occurring with underspecified user queries: the top-ranked results for such queries may not contain documents relevant to the user's search intent, and fresh and relevant pages may not get ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Transactions on the Web

ACM Transactions on the Web Volume 4, Issue 3

July 2010

166 pages

ISSN:1559-1131

EISSN:1559-114X

DOI:10.1145/1806916

Issue’s Table of Contents

Copyright © 2010 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]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 July 2010

Revised: 01 August 2009

Accepted: 01 March 2009

Received: 01 December 2008

Published in TWEB Volume 4, Issue 3

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

17
Total Citations
View Citations
748
Total Downloads

Downloads (Last 12 months)5
Downloads (Last 6 weeks)1

Reflects downloads up to 03 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Dong GMou XZhang HLi RWu HJiang JLi FYu W(2024)Browsing target extraction and spatiotemporal preference mining from the complex virtual trajectoriesInternational Journal of Applied Earth Observation and Geoinformation10.1016/j.jag.2024.103819129(103819)Online publication date: May-2024
https://doi.org/10.1016/j.jag.2024.103819
Dong GLi RWu HChen WHuang WZhang H(2022)Browsing behavior modeling and browsing interest extraction in the trajectories on web map service platformsExpert Systems with Applications: An International Journal10.1016/j.eswa.2022.116590195:COnline publication date: 1-Jun-2022
https://dl.acm.org/doi/10.1016/j.eswa.2022.116590
Yuan ZLiu HLiu JLiu YYang YHu RXiong H(2021)Incremental Spatio-Temporal Graph Learning for Online Query-POI MatchingProceedings of the Web Conference 202110.1145/3442381.3449810(1586-1597)Online publication date: 19-Apr-2021
https://dl.acm.org/doi/10.1145/3442381.3449810
White PRadio E(2021)Mapping Search Queries to Metadata Fields in a GeoBlacklight RepositoryJournal of Library Metadata10.1080/19386389.2020.1915459(1-17)Online publication date: 8-May-2021
https://doi.org/10.1080/19386389.2020.1915459
Viswanathan SOmidvar-Tehrani BBruyat ARoulland FGrasso AWakkary RAndersen KOdom WDesjardins APetersen M(2020)Designing Ambient WandererProceedings of the 2020 ACM Designing Interactive Systems Conference10.1145/3357236.3395518(1405-1418)Online publication date: 3-Jul-2020
https://dl.acm.org/doi/10.1145/3357236.3395518
Feng ZLiu TLi HLu HShou LXu J(2020)Indoor Top-k Keyword-aware Routing Query2020 IEEE 36th International Conference on Data Engineering (ICDE)10.1109/ICDE48307.2020.00109(1213-1224)Online publication date: Apr-2020
https://doi.org/10.1109/ICDE48307.2020.00109
Hao JNiu BQin X(2019)A Keyword-Aware Optimal Route Query Algorithm on Large-Scale Road Networks2019 20th IEEE International Conference on Mobile Data Management (MDM)10.1109/MDM.2019.00124(587-592)Online publication date: Jun-2019
https://doi.org/10.1109/MDM.2019.00124
Sun YZhu HZhuang FGu JHe QGuo YFarooq F(2018)Exploring the Urban Region-of-Interest through the Analysis of Online Map Search QueriesProceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining10.1145/3219819.3220009(2269-2278)Online publication date: 19-Jul-2018
https://dl.acm.org/doi/10.1145/3219819.3220009
Han MYang JFang ZFang Z(2016)Item Sorting Platform Based on Cloud Computing2016 IEEE 13th International Conference on e-Business Engineering (ICEBE)10.1109/ICEBE.2016.053(270-275)Online publication date: Nov-2016
https://doi.org/10.1109/ICEBE.2016.053
Wu DQiao RLi Y(2016)A study on location-based mobile map search behaviorProgram10.1108/PROG-11-2015-007450:3(246-269)Online publication date: 4-Jul-2016
https://doi.org/10.1108/PROG-11-2015-0074
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

EPUB

View this article in ePub.

Media

Figures

Other

Tables

View Issue’s Table of Contents