research-article

Evaluating an associative browsing model for personal information

Authors:

W. Bruce Croft,

Anton BakalovAuthors Info & Claims

CIKM '11: Proceedings of the 20th ACM international conference on Information and knowledge management

Pages 647 - 652

https://doi.org/10.1145/2063576.2063672

Published: 24 October 2011 Publication History

Abstract

Recent studies suggest that associative browsing can be beneficial for personal information access. Associative browsing is intuitive for the user and complements other methods of accessing personal information, such as keyword search. In our previous work, we proposed an associative browsing model of personal information in which users can navigate through the space of documents and concepts (e.g., person names, events, etc.). Our approach differs from other systems in that it presented a ranked list of associations by combining multiple measures of similarity, whose weights are improved based on click feedback from the user.

In this paper, we evaluate the associative browsing model we proposed in the context of known-item finding task. We performed game-based user studies as well as a small scale instrumentation study using a prototype system that helped us to collect a large amount of usage data from the participants. Our evaluation results show that the associative browsing model can play an important role in known-item finding. We also found that the system can learn to improve suggestions for browsing with a small amount of click data.

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Cited By

Dinneen JJulien C(2019)The ubiquitous digital fileJournal of the Association for Information Science and Technology10.1002/asi.2422271:1(E1-E32)Online publication date: 4-Dec-2019
https://dl.acm.org/doi/10.1002/asi.24222
Ochiai SKato MTanaka KLi JWang XGarofalakis MSoboroff ISuel TWang M(2014)Re-call and Re-cognition in Episode Re-retrievalProceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management10.1145/2661829.2661920(579-588)Online publication date: 3-Nov-2014
https://dl.acm.org/doi/10.1145/2661829.2661920
Huangfu YLiu KZhang WZhou PWu YWang QZhu J(2014)LSG: A Unified Multi-dimensional Latent Semantic Graph for Personal Information RetrievalWeb-Age Information Management10.1007/978-3-319-08010-9_60(540-552)Online publication date: 2014
https://doi.org/10.1007/978-3-319-08010-9_60

Index Terms

Evaluating an associative browsing model for personal information
1. Information systems
  1. Information retrieval
    1. Retrieval models and ranking

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cover image ACM Conferences

CIKM '11: Proceedings of the 20th ACM international conference on Information and knowledge management

October 2011

2712 pages

ISBN:9781450307178

DOI:10.1145/2063576

Editors:
Bettina Berendt,
Arjen de Vries,
Wenfei Fan,
Craig Macdonald
University of Glasgow, UK
,
Iadh Ounis
University of Glasgow, UK
,
Ian Ruthven
University of Strathclyde, UK

Copyright © 2011 ACM.

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Publication History

Published: 24 October 2011

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CIKM '11: International Conference on Information and Knowledge Management

October 24 - 28, 2011

Glasgow, Scotland, UK

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Cited By

Dinneen JJulien C(2019)The ubiquitous digital fileJournal of the Association for Information Science and Technology10.1002/asi.2422271:1(E1-E32)Online publication date: 4-Dec-2019
https://dl.acm.org/doi/10.1002/asi.24222
Ochiai SKato MTanaka KLi JWang XGarofalakis MSoboroff ISuel TWang M(2014)Re-call and Re-cognition in Episode Re-retrievalProceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management10.1145/2661829.2661920(579-588)Online publication date: 3-Nov-2014
https://dl.acm.org/doi/10.1145/2661829.2661920
Huangfu YLiu KZhang WZhou PWu YWang QZhu J(2014)LSG: A Unified Multi-dimensional Latent Semantic Graph for Personal Information RetrievalWeb-Age Information Management10.1007/978-3-319-08010-9_60(540-552)Online publication date: 2014
https://doi.org/10.1007/978-3-319-08010-9_60

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