Automated Topic–Document Matching Pipeline for Systematic Literature Reviews

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Authors: Fahad Asmi, Muhammad Azfar anwar
Cited by: 0

Abstract

This code operationalises a computational screening and classification stage of a systematic literature review (SLR). Specifically, it replaces manual thematic assignment with a reproducible, transparent, and auditable workflow. The code is an automated text-mining and topic-matching pipeline designed to support systematic literature reviews by algorithmically aligning full-text research articles with pre-defined LDA topics using semantic similarity and keyword validation.

Fields of Study & Subjects

Computational and Text Analysis Methods Biomedical Text Mining and Ontologies Topic Modeling

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
7 January 2026