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Recognizing user interest and document value from reading and organizing activities in document triage

Published: 29 January 2006 Publication History

Abstract

People frequently must sort through large sets of documents to identify useful materials, for example, when they look through web search results. This document triage process may involve both reading and organizing, possibly using different applications for each activity. Users' interests may be inferred from what they read and how they interact with individual documents; these interests may in turn be used as a basis for identifying other documents or document elements of potential interest within the set. To most effectively identify related documents of interest, activity data must be collected from all applications used in document triage. In this paper we present a common framework (the Interest Profile Manager) for collecting and analyzing user interest. We also present models for detecting user interest based on reading activity alone, on organizing activity alone, and on combined reading and organizing activity. A study comparing document value calculated using the different models shows that incorporating interest information from both reading and organizing activity better predicted users' valuation of documents. This difference was statistically significant when compared to using reading activity alone.

References

[1]
Bae, S., Badi, R., Meintanis, K., Moore, J.M., Zacchi, A., Hsieh, H., Marshall, C., Shipman, F. "Effects of Display Configurations on Document Triage," Proc. of IFIP Interact Conference, 2005, pp. 130--143.
[2]
Chan, P."A Non-Invasive Learning Approach to Building Web User Profiles," Workshop on Web Usage Analysis and User Profiling, 1999, pp. 7--12.
[3]
Claypool, M., Le, P., Waseda, M., Brown, D. "Implicit Interest Indicators," Proc. of ACM Intelligent User Interfaces, 2001, pp. 33--40.
[4]
Goecks, J., Shavlik, J. "Learning Users Interests by Unobtrusively Observing Their Normal Behavior," Proc. of ACM Intelligent User Interfaces, 2000, pp. 129--132.
[5]
Grudin, J. "Groupware and Social Dynamics: Eight Challenges for Developers," Communications of the ACM, 35: 92--105, 1994.
[6]
Kelly, D., Belkin, N. "Display time as implicit feedback: Understanding task effects," Proc. of ACM SIGIR 04, 2004, pp. 377--384.
[7]
Kim, J., Oard, D.W., Romanik, K. "Using implicit feedback for user modeling in internet and intranet searching," University of Maryland CLIS Technical Report, 2000.
[8]
Morita, M., Shinoda, Y. "Information filtering based on user behaviour analysis and best match text retrieval," Proceedings of ACM SIGIR'94, Springer-Verlag, pp. 272--81.
[9]
Nichols, D."Implicit Rating and Filtering," Proc. of the 5th DELOS Workshop on Filtering and Collaborative Filtering, Budapest, Hungary, 10--12, November 1997, pp. 31--36.
[10]
Sarwar, B., Konstan, J., Borchers, A., Herlocker, J., Miller, B., Reidl, J. "Using Filtering Agents to Improve Prediction Quality in the GroupLens Research Collaborative Filtering System," Proc. of ACM Conference on Computer Supported Collaborative Work (CSCW), 1998, pp. 345--354.
[11]
Shipman, F., Hsieh, H., Maloor, P., Moore, J. M. "The Visual Knowledge Builder: A Second Generation Spatial Hypertext," Proc. of ACM Hypertext, 2001, pp. 113--122.
[12]
Shipman, F., Hsieh, H., Moore, J.M., Zacchi, J.M. "Supporting Personal Collections across Digital Libraries in Spatial Hypertext," Proc. of the ACM and IEEE Joint Conference on Digital Libraries, 2004, pp. 358--367.
[13]
Shipman, F., Price, M., Marshall, C., Golovchinsky, G., Schilit, B. "Identifying Useful Passages in Documents Based on Annotation Patterns," Proc. of European Conference on Digital Libraries, Springer Verlag, 2003, pp. 101--112.

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  1. Recognizing user interest and document value from reading and organizing activities in document triage

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        cover image ACM Conferences
        IUI '06: Proceedings of the 11th international conference on Intelligent user interfaces
        January 2006
        392 pages
        ISBN:1595932879
        DOI:10.1145/1111449
        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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        Published: 29 January 2006

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        Author Tags

        1. document triage
        2. information triage
        3. sensemaking
        4. user interest modeling
        5. user interest recognition
        6. visual knowledge builder

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        IUI06: 11th International Conference on Intelligent User Interfaces
        January 29 - February 1, 2006
        Sydney, Australia

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        • (2023)Understanding students’ backtracking behaviors in digital textbooks: a data-driven perspectiveInteractive Learning Environments10.1080/10494820.2023.228096432:10(6717-6734)Online publication date: 15-Nov-2023
        • (2023)Thinking inside the boxJournal of the Association for Information Science and Technology10.1002/asi.2480174:9(1049-1066)Online publication date: 25-May-2023
        • (2021)SumRe: Design and Evaluation of a Gist‐based Summary Visualization for Incident Reports TriageComputer Graphics Forum10.1111/cgf.1430540:3(263-274)Online publication date: 29-Jun-2021
        • (2019)PubMed Text Similarity Model and its application to curation efforts in the Conserved Domain DatabaseDatabase10.1093/database/baz0642019Online publication date: 2-Jul-2019
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        • (2018)Collaborative exploratory search for information filtering and large-scale information triageJournal of the Association for Information Science and Technology10.1002/asi.2396169:3(395-409)Online publication date: 1-Mar-2018
        • (2017)Content Reordering Based on Mouse-tracking for Web ApplicationsAdvances in Science, Technology and Engineering Systems Journal10.25046/aj02031662:3(1314-1322)Online publication date: Aug-2017
        • (2017)Analysis and Modeling of Unified User Interest2017 IEEE International Conference on Information Reuse and Integration (IRI)10.1109/IRI.2017.46(298-307)Online publication date: Aug-2017
        • (2016)User-modeling and recommendation based on mouse-tracking for e-commerce websites2016 19th International Conference on Computer and Information Technology (ICCIT)10.1109/ICCITECHN.2016.7860252(517-523)Online publication date: Dec-2016
        • (2016)An Ontology-Based Framework to Model User Interests2016 International Conference on Computational Science and Computational Intelligence (CSCI)10.1109/CSCI.2016.0082(398-403)Online publication date: Dec-2016
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