research-article

Studying trailfinding algorithms for enhanced web search

Authors:

Jeff HuangAuthors Info & Claims

SIGIR '10: Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval

Pages 443 - 450

https://doi.org/10.1145/1835449.1835524

Published: 19 July 2010 Publication History

Abstract

Search engines return ranked lists of Web pages in response to queries. These pages are starting points for post-query navigation, but may be insufficient for search tasks involving multiple steps. Search trails mined from toolbar logs start with a query and contain pages visited by one user during post-query navigation. Implicit endorsements from many trails can enhance result ranking. Rather than using trails solely to improve ranking, it may also be worth providing trail information directly to users. In this paper, we quantify the benefit that users currently obtain from trail-following and compare different methods for finding the best trail for a given query and each top-ranked result. We compare the relevance, topic coverage, topic diversity, and utility of trails selected using different methods, and break out findings by factors such as query type and origin relevance. Our findings demonstrate value in trails, highlight interesting differences in the performance of trailfinding algorithms, and show we can find best-trails for a query that outperform the trails most users follow. Findings have implications for enhancing Web information seeking using trails.

References

[1]

Agichtein, E., Brill, E. & Dumais, S. (2006). Improving web search ranking by incorporating user behavior information. Proc. SIGIR, 19--26.

Digital Library

[2]

Bates, M.J. (1989). The design of browsing and berrypicking techniques for the online search interface. Online Review, 13(5): 407--424.

[3]

Bilenko, M. & White, R.W. (2008). Mining the search trails of surfing crowds: identifying relevant websites from user activity. Proc. WWW, 51--60.

Digital Library

[4]

Bush, V. (1945). As we may think. Atl. Monthly, 3(2): 37--46.

Digital Library

[5]

Chalmers, M., Rodden, K. & Brodbeck, D. (1998). The order of things: activity-centered information access. Proc. WWW.

Digital Library

[6]

Clarke, C.L.A. et al. (2008). Novelty and diversity in information retrieval evaluation. Proc. SIGIR, 659--666.

Digital Library

[7]

Cole, M. et al. (2009). Usefulness as the criterion for evaluation of interactive information retrieval. Proc. HCIR, 1--4.

[8]

Downey, D., Dumais, S. & Horvitz, E. (2007). Models of searching and browsing: languages, studies, and application. Proc. IJCAI, 2740--2747.

Digital Library

[9]

Fox, S. et al. (2005). Evaluating implicit measures to improve the search experience. TOIS, 23(2): 147--168.

Digital Library

[10]

Freyne, J. et al. (2007). Collecting community wisdom: integrating social search and social navigation. IUI, 52--61.

Digital Library

[11]

Guinan, C. & Smeaton, A.F. (1993). Information retrieval from hypertext using dynamically planned guided tours. Proc. ECHT, 122--130.

Digital Library

[12]

Hammond, N. & Allison, L. (1988). Travels around a learning support environment: rambling, orienteering, or touring? Proc. SIGCHI, 269--273.

Digital Library

[13]

Joachims, T. (2002). Optimizing search engines using click-through data. Proc. SIGKDD, 133--142.

Digital Library

[14]

Joachims, T., Freitag, D. & Mitchell, T. (1997). WebWatcher: a tour guide for the world wide web. Proc. IJCAI, 770--775.

[15]

Olston, C. & Chi, E.H. (2003). ScentTrails: integrating browsing and searching on the web. TOCHI, 10(3): 1--21.

Digital Library

[16]

O'Day, V. & Jeffries, R. (1993). Orienteering in an information landscape: how information seekers get from here to there. Proc. INTERCHI, 438--445.

Digital Library

[17]

Pandit, S. & Olston, C. (2007). Navigation-aided retrieval. Proc. WWW, 391--400.

Digital Library

[18]

Pirolli, P. & Card, S.K. (1999). Information foraging. Psychological Review, 106(4): 643--675.

[19]

Shen, X., Dumais, S. & Horvitz, E. (2005). Analysis of topic dynamics in web search. Proc. WWW, 1102--1103.

Digital Library

[20]

Singhal, A. (2001). Modern information retrieval: a brief overview. Bulletin of the IEEE Computer Society Technical Committee on Data Engineering, 24(4): 35--43.

[21]

Teevan, J. et al. (2004). The perfect search engine is not enough: a study of orienteering behavior in directed search. Proc. SIGCHI, 415--422.

Digital Library

[22]

Trigg, R.H. (1988). Guided tours and tabletops: tools for communicating in a hypertext environment. TOIS, 6(4).

Digital Library

[23]

Vakkari, P. & Taneli, M. (2009). Comparing google to ask-a-librarian service for answering factual and topic questions. Proc. EDCL, 352--363.

Digital Library

[24]

Wang, X. & Zhai, C. (2009). Beyond hyperlinks: organizing information footprints in search logs to support effective browsing. Proc. CIKM, 1237--1246.

Digital Library

[25]

Wexelblat, A. & Maes, P. (1999). Footprints: history-rich tools for information foraging. Proc. SIGCHI, 270--277.

Digital Library

[26]

Wheeldon, R. & Levene, M. (2003). The best trail algorithm for assisted navigation of web sites. Proc. LA-WEB, 166.

Digital Library

[27]

White, R.W., Bilenko, M., & Cucerzan, S. (2007). Studying the use of popular destinations to enhance web search interaction. Proc. SIGIR, 159--166.

Digital Library

[28]

White, R.W. & Drucker, S.M. (2007). Investigating behavioral variability in web search. Proc. WWW, 21--30.

Digital Library

[29]

White, R.W. & Huang, J. (2010). Assessing the scenic route: measuring the value of search trails in web logs. Proc. SIGIR

Digital Library

[30]

Zellweger, P.T. (1989). Scripted documents: a hypermedia path mechanism. Proc. Hypertext, 1--14.

Digital Library

Cited By

White R(2024)Advancing the Search Frontier with AI AgentsCommunications of the ACM10.1145/3655615Online publication date: 20-Aug-2024
https://doi.org/10.1145/3655615
Primbault S(2023)Naviguer dans les savoirs à l’ère numérique. Pour une ethnographie des pratiques informationnelles sur GallicaÉtudes de communication10.4000/edc.16108(61-89)Online publication date: 11-Dec-2023
https://doi.org/10.4000/edc.16108
Piccardi TGerlach MArora AWest R(2023)A Large-Scale Characterization of How Readers Browse WikipediaACM Transactions on the Web10.1145/358031817:2(1-22)Online publication date: 3-Apr-2023
https://dl.acm.org/doi/10.1145/3580318
Show More Cited By

Index Terms

Studying trailfinding algorithms for enhanced web search
1. Information systems
  1. Information retrieval

Recommendations

Assessing the scenic route: measuring the value of search trails in web logs
SIGIR '10: Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval

Search trails mined from browser or toolbar logs comprise queries and the post-query pages that users visit. Implicit endorsements from many trails can be useful for search result ranking, where the presence of a page on a trail increases its query ...
Studying the use of popular destinations to enhance web search interaction
SIGIR '07: Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval

We present a novel Web search interaction feature which, for a given query, provides links to websites frequently visited by other users with similar information needs. These popular destinations complement traditional search results, allowing direct ...
Overlap Among Major Web Search Engines
ITNG '06: Proceedings of the Third International Conference on Information Technology: New Generations

Our study examined the overlap among results retrieved by three major Web search engines for a large set of more than 10,316 queries. Previous smaller studies have discussed the lack of overlap in results returned by Web search engines for the same ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

SIGIR '10: Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval

July 2010

944 pages

ISBN:9781450301534

DOI:10.1145/1835449

General Chairs:
Fabio Crestani
University of Lugano, CH
,
Stéphane Marchand-Maillet
University of Geneva, CH
,
Program Chairs:
Hsin-Hsi Chen
National Taiwan University, TW
,
Efthimis N. Efthimiadis
University of Washington, USA
,
Jacques Savoy
University of Neuchatel, CH

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]

Sponsors

SIGIR: ACM Special Interest Group on Information Retrieval

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 July 2010

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

SIGIR '10

Sponsor:

SIGIR

SIGIR '10: The 33rd International ACM SIGIR conference on research and development in Information Retrieval

July 19 - 23, 2010

Geneva, Switzerland

Acceptance Rates

SIGIR '10 Paper Acceptance Rate 87 of 520 submissions, 17%;

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

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

40
Total Citations
View Citations
475
Total Downloads

Downloads (Last 12 months)8
Downloads (Last 6 weeks)1

Reflects downloads up to 27 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

White R(2024)Advancing the Search Frontier with AI AgentsCommunications of the ACM10.1145/3655615Online publication date: 20-Aug-2024
Primbault S(2023)Naviguer dans les savoirs à l’ère numérique. Pour une ethnographie des pratiques informationnelles sur GallicaÉtudes de communication10.4000/edc.16108(61-89)Online publication date: 11-Dec-2023
Piccardi TGerlach MArora AWest R(2023)A Large-Scale Characterization of How Readers Browse WikipediaACM Transactions on the Web10.1145/358031817:2(1-22)Online publication date: 3-Apr-2023
Shah CWhite RThomas PMitra BSarkar SBelkin N(2023)Taking Search to TaskProceedings of the 2023 Conference on Human Information Interaction and Retrieval10.1145/3576840.3578288(1-13)Online publication date: 19-Mar-2023
Palani SZhou YZhu SDow S(2022)InterWeave: Presenting Search Suggestions in Context Scaffolds Information Search and SynthesisProceedings of the 35th Annual ACM Symposium on User Interface Software and Technology10.1145/3526113.3545696(1-16)Online publication date: 29-Oct-2022
Liu JShah C(2022)Interactive IR User Study Design, Evaluation, and ReportingundefinedOnline publication date: 10-Mar-2022
Wang AZhao YChen Y(2021)Information Search Trail Recommendation Based on Markov Chain Model and Case-based ReasoningData and Information Management10.2478/dim-2020-00475:1(228-241)Online publication date: Jan-2021
Palani SDing ZNguyen AChuang AMacNeil SDow SKitamura YQuigley AIsbister KIgarashi TBjørn PDrucker S(2021)CoNotate: Suggesting Queries Based on Notes Promotes Knowledge DiscoveryProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3445618(1-14)Online publication date: 6-May-2021
Umemoto KYamamoto TTanaka K(2020)Search Support ToolsUnderstanding and Improving Information Search10.1007/978-3-030-38825-6_8(139-160)Online publication date: 30-May-2020
Liu JShah C(2019)Interactive IR User Study Design, Evaluation, and ReportingSynthesis Lectures on Information Concepts, Retrieval, and Services10.2200/S00923ED1V01Y201905ICR06711:2(i-75)Online publication date: 3-Jun-2019
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 Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten