Keyword-Based Journal Categorization Using Deep Learning

Journal searching for particular context is nowadays a very challenging task because of the large availability of journals and also the finding reputed journals with impact factors also one of the tedious job. Our aim is to reduce the long procedure for journal searching using modern techniques. Applications in machine learning have witnessed a booming interest from last decade. The proposed work uses machine learning algorithm with NoSQL database for keyword-based journal retrieval. The complete work is divided into three subworks: (i) keywords modeling, (ii) journal categorization, and (iii) information retrieval of journal. The journal is categorized based on the keyword. The journal and their keywords are trained using deep neural network. For the given keyword, the similar keywords are extracted. The information retrieval gives the details of the journals for the appropriate keywords. The journal details are maintained in the NoSQL database, and the details are retrieved.