Title :
Envisioning user models for adaptive visualization
Author :
Ahn, Jae-wook ; Brusilovsky, Peter
Author_Institution :
Sch. of Inf. Sci., Univ. of Pittsburgh, Pittsburgh, PA
Abstract :
Adaptive search systems apply user models to provide better separation of relevant and non-relevant documents in a list of results. This paper presents our attempt to leverage this ability of user models in the context of visual information analysis. We developed an adaptive visualization approach for presentation and exploration of search results. We simulated a visual intelligence search/analysis scenario with log data extracted from an adaptive information foraging study and were able to verify that our method can improve the ability of traditional relevance visualization to separate relevant and irrelevant information.
Keywords :
data visualisation; information retrieval; search engines; user modelling; Web search context; adaptive search system visualization; information access systems; log data extraction; user model envisioning; user modelling; visual information analysis; visual information browsing environment; visual intelligence analysis scenario; visual intelligence search; Analytical models; Context modeling; Data mining; Data visualization; Graphical user interfaces; Humans; Indexing; Information analysis; Information retrieval; Web search; H.3.1 [Content Analysis and Indexing]: Indexing method; H.3.3 [Information Search and Retrieval]: Information filtering; H.3.5 [Online Information Services]: Web-based services; H.5.2 [User Interfaces]: Graphical user interfaces (GUI); Personalized Search; Query; Relevance feedback; User model; VIBE; Visualization;
Conference_Titel :
Visual Analytics Science and Technology, 2008. VAST '08. IEEE Symposium on
Conference_Location :
Columbus, OH
Print_ISBN :
978-1-4244-2935-6
DOI :
10.1109/VAST.2008.4677373