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Information Processing & Management
Volume 44, Issue 2, March 2008, Pages 511-533
Evaluating Exploratory Search Systems; Digital Libraries in the Context of Users’ Broader Activities
 
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doi:10.1016/j.ipm.2007.07.009    How to Cite or Link Using DOI (Opens New Window)
Copyright © 2007 Elsevier Ltd All rights reserved.

An evaluation of adaptive filtering in the context of realistic task-based information exploration

Daqing Hea, Corresponding Author Contact Information, E-mail The Corresponding Author, Peter Brusilovskya, E-mail The Corresponding Author, Jaewook Ahna, E-mail The Corresponding Author, Jonathan Gradya, E-mail The Corresponding Author, Rosta Farzanb, E-mail The Corresponding Author, Yefei Penga, E-mail The Corresponding Author, Yiming Yangc, E-mail The Corresponding Author and Monica Rogatid, E-mail The Corresponding Author

aSchool of Information Sciences, University of Pittsburgh, 135 N. Bellefield Avenue, Pittsburgh, PA 15256, USA bIntelligence Systems Program, University of Pittsburgh, 5113 Sennott Square, Pittsburgh PA 15260, USA cLanguage Technologies Institute, Machine Learning Department, School of Computer Science, Carnegie Mellon University, Pittsburgh PA 15213, USA dComputer Science Department, School of Computer Science, Carnegie Mellon University, Pittsburgh PA 15213, USA

Received 3 January 2007; 
revised 12 June 2007; 
accepted 9 July 2007. 
Available online 10 September 2007.

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Abstract

Exploratory search increasingly becomes an important research topic. Our interests focus on task-based information exploration, a specific type of exploratory search performed by a range of professional users, such as intelligence analysts. In this paper, we present an evaluation framework designed specifically for assessing and comparing performance of innovative information access tools created to support the work of intelligence analysts in the context of task-based information exploration. The motivation for the development of this framework came from our needs for testing systems in task-based information exploration, which cannot be satisfied by existing frameworks. The new framework is closely tied with the kind of tasks that intelligence analysts perform: complex, dynamic, and multiple facets and multiple stages. It views the user rather than the information system as the center of the evaluation, and examines how well users are served by the systems in their tasks. The evaluation framework examines the support of the systems at users’ major information access stages, such as information foraging and sense-making. The framework is accompanied by a reference test collection that has 18 tasks scenarios and corresponding passage-level ground truth annotations. To demonstrate the usage of the framework and the reference test collection, we present a specific evaluation study on CAFÉ, an adaptive filtering engine designed for supporting task-based information exploration. This study is a successful use case of the framework, and the study indeed revealed various aspects of the information systems and their roles in supporting task-based information exploration.

Keywords: Task-based information exploration; Exploratory search; Evaluation framework; Adaptive filtering; CAFE; User study; Intelligence analysts

Article Outline

1. Introduction
2. Related work
3. An evaluation framework for task-based information exploration
3.1. Reasons for developing the framework
3.2. Methodology
3.3. Metrics
4. A reference test collection
4.1. Document set
4.2. Simulated task scenarios
4.3. Ground truth assessments
5. Evaluating CAFÉ: A sample study
5.1. Data selection and preparation
5.2. Subjects
5.3. Experimental and baseline systems
5.4. Experimental procedure
6. Result analysis
6.1. System comparison based on output ranked lists
6.2. System comparison based on usage profiles
6.3. System comparison based on user feedbacks
7. General discussion and conclusion
Acknowledgements
References
















Information Processing & Management
Volume 44, Issue 2, March 2008, Pages 511-533
Evaluating Exploratory Search Systems; Digital Libraries in the Context of Users’ Broader Activities
 
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