Abstract
Exploratory search is considered challenging for users due to its open-ended nature, and ambiguity of information needs. Clarifying exploratory searchers’ information needs is fundamental to design information environments that provide adaptive support. Since tasks are a representation of information needs, this study investigates the characteristics of exploratory tasks in different fields through multiple attributes to reveal exploratory searchers’ information needs. Repeated surveys were conducted in three representative fields: healthcare, artificial intelligence, and integrated circuit. Content analysis was used to identify 16 attributes. Learning and investigation differ in 14 attributes, and exploratory subtasks differ significantly in Source, Domain knowledge, Cognitive complexity and Search frequency. Different composition of user knowledge background leads to differences in two attributes of Motivation and Cognitive complexity, and difference in the correlation between Motivation and Interdependence. The findings help researchers design distinct exploratory tasks with domain characteristics, and help practitioners develop task- and domain-adaptive exploratory search systems.
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