IntentRadar: Search user interface that anticipates user's search intents

Tuukka Ruotsalo; Jaakko Peltonen; Manuel J A Eugster; Dorota Glowacka; Aki Reijonen; Giulio Jacucci; Petri Myllymäki; Samuel Kaski

doi:10.1145/2559206.2574807

IntentRadar: Search user interface that anticipates user's search intents

Tuukka Ruotsalo, Jaakko Peltonen, Manuel J A Eugster, Dorota Glowacka, Aki Reijonen, Giulio Jacucci, Petri Myllymäki, Samuel Kaski

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

4 Citations (Scopus)

Abstract

We introduce IntentRadar, an interactive search user interface that anticipates user's search intents by estimating them from user interaction. The estimated intents are represented as keywords and visualized on a radial layout that organizes the keywords as directions in the information space. IntentRadar assists users to direct their search by allowing to target relevance feedback on keywords by manipulating the position of the keywords on the radar. The system then learns and visualizes improved estimates of intents and retrieves documents corresponding to the present search intent estimate. IntentRadar has been shown to significantly improve users' task performance and the quality of retrieved information without compromising task execution time.

Original language	English
Title of host publication	CHI EA 2014: One of a ChiNd - Extended Abstracts, 32nd Annual ACM Conference on Human Factors in Computing Systems
Publisher	ACM
Pages	455-458
Number of pages	4
ISBN (Print)	978-1-4503-2474-8
DOIs	https://doi.org/10.1145/2559206.2574807
Publication status	Published - 2014
Publication type	A4 Article in conference proceedings
Event	32nd Annual ACM Conference on Human Factors in Computing Systems, CHI EA 2014 - Duration: 1 Jan 2014 → …

Conference

Conference	32nd Annual ACM Conference on Human Factors in Computing Systems, CHI EA 2014
Period	1/01/14 → …

Keywords

Intent modeling
Interactive information retrieval
Search user interfaces
Visualization

Publication forum classification

Publication forum level 1

Access to Document

10.1145/2559206.2574807

Cite this

Ruotsalo, T., Peltonen, J., Eugster, M. J. A., Glowacka, D., Reijonen, A., Jacucci, G., Myllymäki, P., & Kaski, S. (2014). IntentRadar: Search user interface that anticipates user's search intents. In CHI EA 2014: One of a ChiNd - Extended Abstracts, 32nd Annual ACM Conference on Human Factors in Computing Systems (pp. 455-458). ACM. https://doi.org/10.1145/2559206.2574807

@inproceedings{fa372d5abee6463984f222df8b98bd42,

title = "IntentRadar: Search user interface that anticipates user's search intents",

abstract = "We introduce IntentRadar, an interactive search user interface that anticipates user's search intents by estimating them from user interaction. The estimated intents are represented as keywords and visualized on a radial layout that organizes the keywords as directions in the information space. IntentRadar assists users to direct their search by allowing to target relevance feedback on keywords by manipulating the position of the keywords on the radar. The system then learns and visualizes improved estimates of intents and retrieves documents corresponding to the present search intent estimate. IntentRadar has been shown to significantly improve users' task performance and the quality of retrieved information without compromising task execution time.",

keywords = "Intent modeling, Interactive information retrieval, Search user interfaces, Visualization, Intent modeling, Interactive information retrieval, Search user interfaces, Visualization",

author = "Tuukka Ruotsalo and Jaakko Peltonen and Eugster, {Manuel J A} and Dorota Glowacka and Aki Reijonen and Giulio Jacucci and Petri Myllym{\"a}ki and Samuel Kaski",

year = "2014",

doi = "10.1145/2559206.2574807",

language = "English",

isbn = "978-1-4503-2474-8",

pages = "455--458",

booktitle = "CHI EA 2014: One of a ChiNd - Extended Abstracts, 32nd Annual ACM Conference on Human Factors in Computing Systems",

publisher = "ACM",

address = "United States",

note = "32nd Annual ACM Conference on Human Factors in Computing Systems, CHI EA 2014 ; Conference date: 01-01-2014",

}

Ruotsalo, T, Peltonen, J, Eugster, MJA, Glowacka, D, Reijonen, A, Jacucci, G, Myllymäki, P & Kaski, S 2014, IntentRadar: Search user interface that anticipates user's search intents. in CHI EA 2014: One of a ChiNd - Extended Abstracts, 32nd Annual ACM Conference on Human Factors in Computing Systems. ACM, pp. 455-458, 32nd Annual ACM Conference on Human Factors in Computing Systems, CHI EA 2014, 1/01/14. https://doi.org/10.1145/2559206.2574807

IntentRadar: Search user interface that anticipates user's search intents. / Ruotsalo, Tuukka; Peltonen, Jaakko; Eugster, Manuel J A et al.
CHI EA 2014: One of a ChiNd - Extended Abstracts, 32nd Annual ACM Conference on Human Factors in Computing Systems. ACM, 2014. p. 455-458.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

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T1 - IntentRadar: Search user interface that anticipates user's search intents

AU - Ruotsalo, Tuukka

AU - Peltonen, Jaakko

AU - Eugster, Manuel J A

AU - Glowacka, Dorota

AU - Reijonen, Aki

AU - Jacucci, Giulio

AU - Myllymäki, Petri

AU - Kaski, Samuel

PY - 2014

Y1 - 2014

N2 - We introduce IntentRadar, an interactive search user interface that anticipates user's search intents by estimating them from user interaction. The estimated intents are represented as keywords and visualized on a radial layout that organizes the keywords as directions in the information space. IntentRadar assists users to direct their search by allowing to target relevance feedback on keywords by manipulating the position of the keywords on the radar. The system then learns and visualizes improved estimates of intents and retrieves documents corresponding to the present search intent estimate. IntentRadar has been shown to significantly improve users' task performance and the quality of retrieved information without compromising task execution time.

AB - We introduce IntentRadar, an interactive search user interface that anticipates user's search intents by estimating them from user interaction. The estimated intents are represented as keywords and visualized on a radial layout that organizes the keywords as directions in the information space. IntentRadar assists users to direct their search by allowing to target relevance feedback on keywords by manipulating the position of the keywords on the radar. The system then learns and visualizes improved estimates of intents and retrieves documents corresponding to the present search intent estimate. IntentRadar has been shown to significantly improve users' task performance and the quality of retrieved information without compromising task execution time.

KW - Intent modeling

KW - Interactive information retrieval

KW - Search user interfaces

KW - Visualization

KW - Intent modeling

KW - Interactive information retrieval

KW - Search user interfaces

KW - Visualization

U2 - 10.1145/2559206.2574807

DO - 10.1145/2559206.2574807

M3 - Conference contribution

AN - SCOPUS:84900560093

SN - 978-1-4503-2474-8

SP - 455

EP - 458

BT - CHI EA 2014: One of a ChiNd - Extended Abstracts, 32nd Annual ACM Conference on Human Factors in Computing Systems

PB - ACM

T2 - 32nd Annual ACM Conference on Human Factors in Computing Systems, CHI EA 2014

Y2 - 1 January 2014

ER -

IntentRadar: Search user interface that anticipates user's search intents

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Keywords

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Cite this