A Tool for Customized Searching of Research Articles (ASSORT)

Knowledge in the literature is increasing day by day. Even if it is a positive situation, the diversity and quantity of information makes it difficult to retrieve the useful information. This diversity manifests itself even in scientific articles in the same domain. Our aim in this study is to provide a better user experience to rank the most relevant scientific articles for a user given query. To achieve this goal we developed a Natural Language Processing (NLP) based approach to rank relevant articles by making use of an abstract provided by the user.

Poster: https://drive.google.com/file/d/1GHyvXtDPMEGgoNvnlnwi-mNd8rPIKx97/view?usp=sharing

Video: https://drive.google.com/file/d/1J43PiW9c-PGXhzGqDm2qvxzdtbIEV7Ur/view?usp=sharing