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Ahmad, Manar Talat
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Computer Science & IT Electrical & Electronics Engineering

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A Recommendation System for University Discussion Committees Mundher, Zaid; Ahmad, Manar Talat
Sistemasi: Jurnal Sistem Informasi Vol 13, No 6 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i6.4726

Abstract

One of the topics that have emerged and gained popularity in recent years, due to the extensive availability of data, is recommendation systems. The concept of recommendation systems is based on saving users' time and effort while using the Internet for browsing, shopping, or other web activities. On the other hand, one of the routine tasks that is consistently performed in the academic community is the selection of committees’ members for the defense of master's thesis or doctoral dissertations. These committees are responsible for evaluating the graduate students’ work and assessment of the academic and research efforts. In general, naming discussion committees' members is one of the challenges that used to be solved manually. In this work, a recommendation system was built to propose a discussion committee’s members at Computer Science department in University of Mosul based on a dataset that includes the committees that were previously named. Two methods were introduced, developed, and tested based on content-based recommendation system techniques and cluster-based recommendation system techniques.
A Large-Scale Open Dataset of Computer Science Research Papers (2020–2025) Mundher, Zaid; Ahmad, Manar Talat
Sistemasi: Jurnal Sistem Informasi Vol 15, No 4 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i4.6255

Abstract

The rapid growth of publications in different fields, such as computer science, required well-structured datasets to support data-driven research. This paper presents an open large-scale dataset of computer science research papers published between 2020 and 2025, collected from Crossref metadata using the Crossref REST API. A structured keyword-based retrieval framework was developed to collect papers and their associated metadata. Preprocessing techniques, including cleaning, normalization, and validation were also made on the collected data. The introduced dataset has 4,313,328 research paper records which represents one of the largest structured collections of computer science publications for the specified period. The dataset provides comprehensive metadata fields that enable large-scale analysis, research trend identification, collaboration network exploration, and the recommendation systems development.
Co-Authors Mundher, Zaid