Smart Scholar: A Modern Approach to Research Paper Recommendations

References

[1] Ramos J (2003) Using TF-IDF to determine word relevance in document queries. In: Proc. of the first int. conf. on machine learning.

[2] S. Bahulikar, ”Analyzing recommender systems and applying a location based ap- proach using tagging”, 2017 2nd International Conference for Convergence in Tech- nology (I2CT), 2017.

[3] R. K. Mysore, M. Junichiro and S. Ichiro, ”Cross-Domain Academic Paper Recom- mendation by Semantic Linkage Approach Using Text Analysis and Recurrent Neural Networks”, Management of Engineering and Technology (PICMET) 2017 Portland International Conference on, 2017.

[4] Y. C. Lee et al., ”Recommendation of research papers in DBpia: A Hybrid approach exploiting content and collaborative data”, 2016 IEEE International Conference on Systems Man and Cybernetics SMC 2016 - Conference Proceedings, pp. 2966-2971, 2017.

[5] W. Zhao, R. Wu and H. Liu, ”Paper recommendation based on the knowledge gap be- tween a researchers background knowledge and research target”, Inf. Process. Manag., vol. 52, no. 5, pp. 976-988, 2016.

[6] J. D. West, I. Wesley-Smith and C. T. Bergstrom, ”A Recommendation System Based on Hierarchical Clustering of an Article-Level Citation Network”, IEEE Trans. Big Data, vol. 2, no. 2, pp. 113-123, 2016.

[7] W. Zhang, T. Yoshida and X. Tang, ”A comparative study of TF*IDF LSI and multi- words for text classification”, Expert Syst. Appl., vol. 38, no. 3, pp. 2758-2765, 2011.

[8] C.-H. HUANG, J. YIN and F. HOU, ”A text similarity measurement combining word semantic information with TF-IDF method”, Chinese Journal of Computers, 2011

[9] M. Ohta, T. Hachiki and A. Takasu, ”Related paper recommendation to support online-browsing of research papers”, 4th International Conference on the Applications of Digital Information and Web Technologies ICADIWT 2011, pp. 130-136, 2011.

@article{1705889,
      author = {Manyar Abuzar, Adil Khatik, Puja Borse, Komal Mali, Sapna Mali; Prof. S. V. Chudhari},
      title = {Smart Scholar: A Modern Approach to Research Paper Recommendations},
      journal = {Iconic Research And Engineering Journals},
      year = {2024},
      volume = {7},
      number = {12},
      pages = {66-69},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1705889.pdf},
      abstract = {Traditional methods of accessing scholarly literature through manual searching have become increasingly inefficient in the face of the exponential growth of research articles. In response, this paper presents a comprehensive approach to developing a research paper recommender system. Motivated by the desire to alleviate information overload for researchers, our system leverages natural language processing techniques to streamline the literature exploration process. Through rigorous evaluation and testing, we demonstrate the effectiveness of our system in providing personalized recommendations tailored to user preferences. Our work not only addresses the limitations of existing systems but also lays the groundwork for future advancements in the field of scholarly literature exploration.},
      keywords = {Clustering, Similarity Measure},
      month = {June},
  }