Research Article

NLP-Based Problem-Solution Relationship Extraction and Mapping in Computer Architecture Literature

Volume: 10 Number: 1 August 31, 2026
EN TR

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

  1. [1] B. Kolukisa, B. K. Dedeturk, B. A. Dedeturk, A. Gulsen, and G. Bakal, A comparative analysis on medical article classification using text mining & machine learning algorithms, in: 2021 6th International Conference on Computer Science and Engineering (UBMK), IEEE, 2021, pp. 360–365.
  2. [2] İnal, Y., Bakal, G., and Eşit, M., Multi-Method Text Summarization: Evaluating Extractive and BART-Based Approaches on CNN/Daily Mail, in: 2025 9th International Symposium on Innovative Approaches in Smart Technologies (ISAS), IEEE, 2025, pp. 1-7.
  3. [3] C. Yiran, Y. Xie, L. Song, F. Chen, and T. Tang., A survey of accelerator architectures for deep neural networks, Engineering 6 (3) (2020) 264–274.
  4. [4] S. Mittal, A survey of ReRAM-based architectures for processing-in-memory and neural network acceleration, Machine learning and knowledge extraction 1 (2018) 75–114.
  5. [5] J. Cong, M. A. Ghodrat, M. Gill, B. Grigorian, and G. Reinman, Accelerator-rich architectures:Opportunities and progresses, in: 2014 51st ACM/EDAC/IEEE Design Automation Conference(DAC), IEEE, 2014, pp. 1–6.
  6. [6] M. Grootendorst, BERTopic: Neural topic modeling with a class-based TF-IDF procedure, arXiv preprint arXiv:2203.05794, 2022.
  7. [7] N. Reimers and I. Gurevych, Sentence-BERT: Sentence embeddings using Siamese BERT-networks, in: Proceedings of the 2019 conference on empirical methods in natural language processing and the 9th international joint conference on natural language processing (EMNLP-IJCNLP), ACL, 2019, pp. 3982–3992.
  8. [8] M. Karabacak and K. Margetis, Natural language processing reveals research trends and topics in the spine journal over two decades: a topic modeling study, The Spine Journal 24 (3) (2024) 397–405.

Details

Primary Language

English

Subjects

Data Mining and Knowledge Discovery, Natural Language Processing

Journal Section

Research Article

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

APA
Oudjana, Y., & Bakal, M. G. (2026). NLP-Based Problem-Solution Relationship Extraction and Mapping in Computer Architecture Literature. International Journal of Multidisciplinary Studies and Innovative Technologies, 10(1), 97-101. https://doi.org/10.36287/ijmsit.10.1.11
AMA
1.Oudjana Y, Bakal MG. NLP-Based Problem-Solution Relationship Extraction and Mapping in Computer Architecture Literature. IJMSIT. 2026;10(1):97-101. doi:10.36287/ijmsit.10.1.11
Chicago
Oudjana, Yassine, and Mehmet Gökhan Bakal. 2026. “NLP-Based Problem-Solution Relationship Extraction and Mapping in Computer Architecture Literature”. International Journal of Multidisciplinary Studies and Innovative Technologies 10 (1): 97-101. https://doi.org/10.36287/ijmsit.10.1.11.
EndNote
Oudjana Y, Bakal MG (August 1, 2026) NLP-Based Problem-Solution Relationship Extraction and Mapping in Computer Architecture Literature. International Journal of Multidisciplinary Studies and Innovative Technologies 10 1 97–101.
IEEE
[1]Y. Oudjana and M. G. Bakal, “NLP-Based Problem-Solution Relationship Extraction and Mapping in Computer Architecture Literature”, IJMSIT, vol. 10, no. 1, pp. 97–101, Aug. 2026, doi: 10.36287/ijmsit.10.1.11.
ISNAD
Oudjana, Yassine - Bakal, Mehmet Gökhan. “NLP-Based Problem-Solution Relationship Extraction and Mapping in Computer Architecture Literature”. International Journal of Multidisciplinary Studies and Innovative Technologies 10/1 (August 1, 2026): 97-101. https://doi.org/10.36287/ijmsit.10.1.11.
JAMA
1.Oudjana Y, Bakal MG. NLP-Based Problem-Solution Relationship Extraction and Mapping in Computer Architecture Literature. IJMSIT. 2026;10:97–101.
MLA
Oudjana, Yassine, and Mehmet Gökhan Bakal. “NLP-Based Problem-Solution Relationship Extraction and Mapping in Computer Architecture Literature”. International Journal of Multidisciplinary Studies and Innovative Technologies, vol. 10, no. 1, Aug. 2026, pp. 97-101, doi:10.36287/ijmsit.10.1.11.
Vancouver
1.Yassine Oudjana, Mehmet Gökhan Bakal. NLP-Based Problem-Solution Relationship Extraction and Mapping in Computer Architecture Literature. IJMSIT. 2026 Aug. 1;10(1):97-101. doi:10.36287/ijmsit.10.1.11