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From Search to Discovery with Visual Exploration Tools

Published: 13 March 2017 Publication History

Abstract

In our goal to personalize the discovery of scientific information, we built systems using visual analytics principles for exploration of textual documents [1]. The concept was extended to explore information quality of user generated content [2]. Our interfaces build upon a cognitive model, where awareness is a key step of exploration [3]. In education-related circles, a frequent concern is that people increasingly need to know how to search, and that knowing how to search leads to finding information efficiently. The ever-growing information overabundance right at our fingertips needs a natural skill to develop and refine search queries to get better search results, or does it? Exploratory search is an investigative behavior we adopt to build knowledge by iteratively selecting interesting features that lead to associations between representative items in the information space [4,5]. Formulating queries was proven more complicated for humans than recognizing information visually [6]. Visual analytics takes the form of an open ended dialog between the user and the underlying analytics algorithms operating on the data [7]. This talk describes studies on exploration and discovery with visual analytics interfaces that emphasize transparency and control features to trigger awareness. We will discuss the interface design and the studies of visual exploration behavior.

References

[1]
di Sciascio, C, Sabol, V.and Veas, E. 2016. Rank As You Go : User-Driven Exploration of Search Results. In Proc. IUI '16. 118--129.
[2]
di Sciascio, C, Strohmeier D., Errecalde, M, and Veas, E. 2017 WikiLyzer: Interactive Information Quality Assessment in Wikipedia. In Proc. IUI '17. To appear.
[3]
di Sciascio, C., Sabol, V., and Veas, E. 2017. Supporting Exploratory Search with a Visual User-Driven Approach. ACM Trans. Interact. Intell. Syst. 9, 4, 39 (to appear).
[4]
Marchionini, G. Exploratory search: from finding to understanding. Communications of the ACM, 49 (4). 41--46.
[5]
Pirolli, P. and Card.S. 2005. The sensemaking process and leverage points for analyst technology as identified through cognitive task analysis. (2005), 2--4.
[6]
Hearst, M. 2009. Search User Interfaces (1st ed.). Cambridge University Press, New York, NY, USA.
[7]
Thomas, J. and Cook, K.A. Illuminating the path: The research and development agenda for visual analytics. Ed. by James

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Published In

cover image ACM Conferences
ESIDA '17: Proceedings of the 2017 ACM Workshop on Exploratory Search and Interactive Data Analytics
March 2017
82 pages
ISBN:9781450349031
DOI:10.1145/3038462
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 March 2017

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Author Tags

  1. exploratory search
  2. information foraging
  3. sensemaking
  4. visual exploration

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  • Invited-talk

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  • EC 2020

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IUI'17
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IUI '25

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