• SELVI R
• RITHIK HARENDAR M
• SETHUMADAV S

In this era of vast scholarly research output, efficient retrieval of relevant journal papers remains a significant challenge. This project introduces a novel approach to journal paper search systems, aiming to not only retrieve papers based on similarity but also enhance originality and minimize plagiarism concerns. The proposed system operates by accepting document abstracts as input and employs a combination of deep learning techniques for classification, Siamese network, and recommendation.The system begins by utilizing an LSTM (Long Short-Term Memory) classifier to accurately categorize the domain of the input document. Following domain classification, a Siamese Network is applied to find similar documents together, thus facilitating a focused search approach. Moreover, the system calculates similarity scores between the input abstract and the base papers, considering both content and publication year.Furthermore, to mitigate the risk of plagiarism and promote originality, the system incorporates a recommendation engine. This engine not only suggests papers with high similarity scores but also provides insightful recommendations for augmenting the user's project. By suggesting additional ideas and perspectives to incorporate into the user's work, the system promotes originality and guards against potential plagiarism pitfalls.In summary, this project presents an innovative journal paper search system that not only retrieves relevant papers efficiently but also fosters originality in academic research by providing tailored recommendations for project enhancement

Document Retrieval, Research Papers, LSTM,, Deep Learning, Similarity Score, NLP,

"Research Navigator : Automated Research paper Recommendation System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.k521-k525, April-2024, Available :http://www.jetir.org/papers/JETIR2404A70.pdf

"Research Navigator : Automated Research paper Recommendation System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppk521-k525, April-2024, Available at : http://www.jetir.org/papers/JETIR2404A70.pdf