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Smart Scholar: A Modern Approach to Research Paper Recommendations
Subject area: Science,Engineering and Technology · Area of research: Machine Learning, Natural Language Processing
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
How to cite this paper
@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},
}