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Findex: search result categories help users when document ranking fails

Published: 02 April 2005 Publication History

Abstract

Long web search result lists can be hard to browse. We demonstrated experimentally, in a previous study, the usefulness of a categorization algorithm and filtering interface. However, the nature of interaction in real settings is not known from an experiment in laboratory settings. To address this problem, we provided our categorizing web search user interface to 16 users for a two month period. The interactions with the system were logged and the users' opinions were elicited with two questionnaires. The results show that categories are successfully used as part of users' search habits. They are helpful when the result ranking of the search engine fails. In those cases, the users are able to access results that locate far in the rank order list with the categories. Users can also formulate simpler queries and find needed results with the help of the categories. In addition, the categories are beneficial when more than one result is needed like in an exploratory or undirected search task.

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cover image ACM Conferences
CHI '05: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
April 2005
928 pages
ISBN:1581139985
DOI:10.1145/1054972
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: 02 April 2005

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Author Tags

  1. categorization
  2. clustering
  3. information access
  4. search user interfaces
  5. web search

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CHI '05 Paper Acceptance Rate 93 of 372 submissions, 25%;
Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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  • (2024)Properties and Styles of Software Technology TutorialsIEEE Transactions on Software Engineering10.1109/TSE.2023.333256850:2(159-172)Online publication date: Feb-2024
  • (2023)Differentiable Topics Guided New Paper RecommendationNeural Information Processing10.1007/978-981-99-8076-5_4(44-56)Online publication date: 14-Nov-2023
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