NLP-Based Problem-Solution Relationship Extraction and Mapping in Computer Architecture Literature
Abstract
Research in computer architecture typically follows a structured approach, addressing narrowly defined problems with specialized solutions. Because these articles exhibit consistent writing patterns, they are highly suitable for automated analysis. In this paper, a natural language processing (NLP) workflow is presented for classifying research papers based on the specific problems they investigate and the solutions they propose. By mapping these problem-solution relationships across a large corpus of articles, the proposed approach identifies frequently studied pairings, reveals historical research trends, and uncovers potential gaps in the literature, thereby helping direct future academic work.
Keywords
References
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Details
Primary Language
English
Subjects
Data Mining and Knowledge Discovery, Natural Language Processing
Journal Section
Research Article
Authors
Yassine Oudjana
0009-0004-2148-7636
Türkiye
Early Pub Date
August 13, 2026
Publication Date
August 31, 2026
Submission Date
June 30, 2026
Acceptance Date
August 13, 2026
Published in Issue
Year 2026 Volume: 10 Number: 1