A Semi-automatic Document Screening System for Computer Science Systematic Reviews

An analysis of work saved over sampling in the evaluation of automated citation screening in systematic literature reviews

“…Our harmonised data loaders selectively load the PubMed articles that are a part of each dataset. The single exception is the dataset by Hannousse and Yahiouche [22], which is the only publicly available collection of non-medical SLRs. For this dataset, we extract the content using the SemanticScholar API.…”

“…So far, there has been little attention to review automation outside of the medical domain. The only available datasets are four social science reviews by Miwa et al [53], and seven computer science reviews by Hannousse and Yahiouche [22]. Compared to the general interest and rate of production of SLRs in other domains, this overall underrepresentation of benchmark datasets could be improved.…”

“…In recent years, there has been an increasing interest in automating the SLR process [78,59,55,22,2], with works often focusing on improving the CS step by (a) using machine learning (ML) [43,44], (b) natural language processing (NLP) [27,36,77], and (c) information retrieval (IR) [68,88] techniques. Automated CS systems have the potential to significantly reduce the time and resources required for this critical step, thereby speeding up the SLRs production [73].…”

Perpustakaan Digital dalam Pendidikan Tinggi: Analisis Bibliometrik

“…Mereka menyimpan dan memberikan akses ke sumber daya penting seperti jurnal ilmiah, buku elektronik, tesis, dan materi pembelajaran online. Otomatisasi sistem yang diterapkan dalam perpustakaan digital sangat penting untuk dapat dimanfaatkan olegh civitas akademika di perguruan tinggi (Ferilli et al, 2017;Hannousse & Yahiouche, 2022;Vovk & Prychun, 2023). Dalam konteks ini, pemetaan penelitian akan membantu memahami sejauh mana perpustakaan digital telah berkembang dan sejauh mana dampaknya terhadap pendidikan tinggi.…”