An Interdisciplinary Study to Observe Users’ Online Search Tasks and Behavior for the Design of an IS&R Framework

Abstract

The Web is the world’s largest data repository, and search engines are regarded as key tools for finding and extracting useful information from the tremendous amount of available data. In recent years, user-oriented Information Seeking (IS) research methods rooted in the social sciences have been integrated with computer science-based Information Retrieval (IR) approaches to capitalize on the strengths of both fields. The concept is called the Information Seeking and Retrieval (IS&R) framework. Pilot research models in the IS research area show that workers’ information seeking activities exhibit common patterns. In this study, we will systematically identify and categorize important theoretical frameworks of IS&R. Based on the observations of IS&R studies, we propose implicit and explicit evolving topic-needs determination methods. The methods consider personal factors, and content factors simultaneously in order to fulfil the user’s evolving information needs precisely. The research contributes to design the retrieval functions based on the IS&R models for supplying documents for knowledge-intensive tasks.