A Context-Aware System for Selective Dissemination of Information in Electronic Theses and Dissertations

Sadeghi Pouryani, Abbas; Zarinbal, Marzieh

doi:10.22034/jipm.2025.2047228.1865

A Context-Aware System for Selective Dissemination of Information in Electronic Theses and Dissertations

Document Type : Original Article

Authors

Abbas Sadeghi Pouryani ¹

Marzieh Zarinbal ²

¹ Iranian Research Institute for Information Science and Technology (IranDoc); Tehran, Iran.

² Amirkabir University of Technology, Faculty of Industrial Engineering and Management Systems; Tehran, Iran; Iranian Research Institute for Information Science and Technology (IranDoc); Tehran, Iran.

10.22034/jipm.2025.2047228.1865

Abstract

In an electronic dissertation and thesis (ETDs) system, selective dissemination of information is the delivery of ETD documents to users which are more likely to be useful to those users. This research aims to present a model for selective dissemination of information using user and ETD contexts in an ETD database. The core of this model is a context-aware content-based recommender system in which the ETD contexts are compared with the user contexts, and the target users with a higher likelihood of being useful are selected. The research method is a design science study in which an artifact (software system) is built and the research contribution is the user and ETD context model for the ETDs system. In the selective dissemination of information, user contexts and ETD contexts were weighted and compared based on the proposed method of this paper, CF-ICF, to select the users closest to the ETD. From the published ETDs of the Iranian academic year 1401-1402, 10,860 ETDs were randomly selected. The 30 ETDs with the highest similarity between the ETD context and the user context were sent to each user for feedback. The results indicate that the first recommendations were highly beneficial to users in at least 56% of cases. For these recommendations, the precision is 0.73 out of 1, and the Normalized Discount Cumulative Gain index is 0.69 out of 1. This method provides a model selective dissemination of information based on the context of users and the context of ETDs, achieving optimal precision in the first five recommendations. It can be highly beneficial for developers and system administrators of ETDs.

Keywords

Context-Aware Recommender

Dissertation and Thesis Database

Selective Dissemination of Information

Subjects

Smart and Recommender Systems

فهرست منابع

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