dc.description.abstract |
With the continuous evolution of learning trends, students are encouraged to carry out
research and development-based projects all by themselves. It requires credible
resources from research databases like IEEEXplore, Science Direct, and Google
Scholar. For a young researcher starting, the usage of such research databases to find
accurate information can be very time-consuming. Hence this project aims to resolve
this issue by developing a virtual research assistant chatbot.
A chatbot is an interactive conversational program that carries out conversations with
humans in a friendly way, much like a human assistant. Chatbot applications are
developed to facilitate information-gathering about products and services across
several fields. However, there have been no reports or findings related to the
development of chatbots in the research sector.
Therefore, a prototype of a virtual research assistant chatbot has been developed in
this project. It aims at bridging this research gap between young researchers and
research databases. It focuses on integrating the chat interface with a python based
ranking model. Dialogflow is the considered chatbot framework, and the fulfilment
feature facilitates communication to the ranking model. The model developed should
make calls to the Scopus database to retrieve research articles, according to the
identified research field or author name extracted from the conversation by matching
it to the trained intents and entities. Additionally, it intends to rank the research
content using the TF-IDF algorithm for relevancy, thereby significantly influencing
the efficiency of researchers.
Based on their evaluation, it was found that the performance level was good and the
accuracy of the results obtained was satisfactory. The response time is really low
compared to other ways of finding research materials. Therefore, this qualitative
research-based project has enabled in initiating the development of a research-based
chatbot application for professional researchers. This can pave the way for many more
relevant opportunities and future enhancements for chatbot in research. |
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