For early-career students and researchers, accessing academic databases to identify articles on a specific topic is an everyday task. However, the nature of the scholarly databases, e.g., cost, access restrictions, and complexities in the search strategies, often discourages new users from using these databases efficiently.
To retrieve any scholarly articles, the first step involves identifying the appropriate database to perform a search using relevant keywords, often known as findability. In addition, the location of these databases is mandatory to know before even searching. However, early-career students find it challenging to identify the location of these databases. Universities and libraries maintain a list of database catalogues depending on relevant subjects and keywords, but they are often in a messy format or require reading a lot of unnecessary documentation.
This project aims to develop a chatbot called askit4info that can accept very short commands from users, suggest relevant databases and associated search keywords, and assist users in retrieving scholarly articles with minimum cognitive efforts.