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Title: Analyzing the Information Search Behavior and Intentions in Visual Information Systems
Authors: Kawa Nazemi, Dirk Burkhardt, Arjan Kuijper
Journal: Journal of computer science technology updates
Publisher: Cosmos Scholars Publishing House
Year: 2017
Volume: 4
Issue: 2
Language: en
Keywords: Information RetrievalPredictive AnalysisInformation search behaviorHuman-computer-interactionInteractive searchUser-centered-designAdaptive visualizationDistant supervision
Visual information search systems support different search approaches such as targeted, exploratory or analytical search. Those visual systems deal with the challenge of composing optimal initial result visualization sets that face the search intention and respond to the search behavior of users. The diversity of these kinds of search tasks require different sets of visual layouts and functionalities, e.g. to filter, thrill-down or even analyze concrete data properties. This paper describes a new approach to calculate the probability towards the three mentioned search intentions, derived from users’ behavior. The implementation is realized as a web-service, which is included in a visual environment that is designed to enable various search strategies based on heterogeneous data sources. In fact, based on an entered search query our developed search intention analysis web-service calculates the most probable search task, and our visualization system initially shows the optimal result set of visualizations to solve the task. The main contribution of this paper is a probability-based approach to derive the users’ search intentions based on the search behavior enhanced by the application to a visual system.
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