[Objective] This paper investigates the users’ information needs, searching behaviors, and preferences, aiming to identify their expectations accurately. [Methods] First, we took the perceived usefulness and ease of use from the technology acceptance model (TAM) as the theoretical framework. Then, we used surveys, server log analysis, and the vocal thinking method to study the expectations of information demands, searching behaviors and acceptance preference of users in different scenarios. Finally, we conducted expert interviews to construct users’ portrait model based on the vector space model (VSM). [Results] The proposed method helped us recommend scenarios for different users effectively with the collaborative filtering algorithm and the Tagul tool. [Limitations] The experimental sample size is small, which might affect the accuracy of recommendation. [Conclusions] The proposed model clusters users’ expectation of information and recommends scenario-based services for mobile library users.
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