Article

Navigation in degree of interest trees

Authors:

Raluca Budiu,

Peter Pirolli,

Michael FleetwoodAuthors Info & Claims

AVI '06: Proceedings of the working conference on Advanced visual interfaces

Pages 457 - 462

https://doi.org/10.1145/1133265.1133358

Published: 23 May 2006 Publication History

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Abstract

We present an experiment that compares how people perform search tasks in a degree-of-interest browser and in a Windows-Explorer-like browser. Our results show that, whereas users do attend to more information in the DOI browser, they do not complete the task faster than in an Explorer-like browser. However, in both types of browser, users are faster to complete high information scent search tasks than low information scent tasks. We present an ACT-R computational model of the search task in the DOI browser. The model describes how a visual search strategy may combine with semantic aspects of processing, as captured by information scent. We also describe a way of automatically estimating information scent in an ontological hierarchy by querying a large corpus (in our case, Google's corpus).

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Cited By

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Pirolli P(2018)Information ForagingEncyclopedia of Database Systems10.1007/978-1-4614-8265-9_205(1930-1936)Online publication date: 7-Dec-2018
https://doi.org/10.1007/978-1-4614-8265-9_205
Pirolli P(2017)Information ForagingEncyclopedia of Database Systems10.1007/978-1-4899-7993-3_205-2(1-7)Online publication date: 3-Jan-2017
https://doi.org/10.1007/978-1-4899-7993-3_205-2
Gamallo PBordag S(2011)Is singular value decomposition useful for word similarity extraction?Language Resources and Evaluation10.1007/s10579-010-9129-545:2(95-119)Online publication date: 1-May-2011
https://dl.acm.org/doi/10.1007/s10579-010-9129-5
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Navigation in degree of interest trees

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Eye tracking studies of the Hyperbolic Tree browser [10] suggest that visual search in focus+context displays is highly affected by information scent (i.e., local cues, such as text summaries, used to assess and navigate toward distal information ...

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Published In

AVI '06: Proceedings of the working conference on Advanced visual interfaces

May 2006

512 pages

ISBN:1595933530

DOI:10.1145/1133265

General Chair:
Augusto Celentano
Università Ca' Foscari di Venezia, Mestre(VE), Italy

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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 May 2006

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AVI06

AVI06: The International Conference on Advanced Visual Interfaces

May 23 - 26, 2006

Venezia, Italy

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Overall Acceptance Rate 128 of 490 submissions, 26%

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Pirolli P(2018)Information ForagingEncyclopedia of Database Systems10.1007/978-1-4614-8265-9_205(1930-1936)Online publication date: 7-Dec-2018
https://doi.org/10.1007/978-1-4614-8265-9_205
Pirolli P(2017)Information ForagingEncyclopedia of Database Systems10.1007/978-1-4899-7993-3_205-2(1-7)Online publication date: 3-Jan-2017
https://doi.org/10.1007/978-1-4899-7993-3_205-2
Gamallo PBordag S(2011)Is singular value decomposition useful for word similarity extraction?Language Resources and Evaluation10.1007/s10579-010-9129-545:2(95-119)Online publication date: 1-May-2011
https://dl.acm.org/doi/10.1007/s10579-010-9129-5
Otero P(2009)Comparing Different Properties Involved in Word Similarity ExtractionProceedings of the 14th Portuguese Conference on Artificial Intelligence: Progress in Artificial Intelligence10.1007/978-3-642-04686-5_52(634-645)Online publication date: 7-Oct-2009
https://dl.acm.org/doi/10.1007/978-3-642-04686-5_52
Pirolli P(2009)Information ForagingEncyclopedia of Database Systems10.1007/978-0-387-39940-9_205(1485-1490)Online publication date: 2009
https://doi.org/10.1007/978-0-387-39940-9_205
Halverson THornof ACzerwinski MLund ATan D(2008)The effects of semantic grouping on visual searchCHI '08 Extended Abstracts on Human Factors in Computing Systems10.1145/1358628.1358876(3471-3476)Online publication date: 5-Apr-2008
https://dl.acm.org/doi/10.1145/1358628.1358876
Elmqvist NHenry NRiche YFekete JCzerwinski MLund ATan D(2008)MelangeProceedings of the SIGCHI Conference on Human Factors in Computing Systems10.1145/1357054.1357263(1333-1342)Online publication date: 6-Apr-2008
https://dl.acm.org/doi/10.1145/1357054.1357263
Budiu RRoyer CPirolli P(2007)Modeling information scentLarge Scale Semantic Access to Content (Text, Image, Video, and Sound)10.5555/1931390.1931422(314-332)Online publication date: 30-May-2007
https://dl.acm.org/doi/10.5555/1931390.1931422

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The effects of information scent on visual search in the hyperbolic tree browser

The scent of a site: a system for analyzing and predicting information scent, usage, and usability of a Web site

Visual information foraging in a focus + context visualization

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