Abstract
Finding one of the best projects to work on which actually are germane to the students and specifically those topics which are also trending is one of the most onerous tasks to achieve. Students spend most of their time researching what projects to work on to select the best out of the topics pertinent to them. The proposed system aims to solve this problem with the help of an intelligent conversational system that captures and analyzes the student’s interests and then recommends the project topics by displaying various research papers and other reasonably key websites. The system has a chatbot that precisely captures the user’s interests and derives the keywords based on the user information. The system then essentially uses Google Custom Search API which ranks the results. The final results are then displayed by incorporating the importance and weightage of the keywords and user likings extracted. Thus, the proposed model displays the results that align with the user interests and predilection thereby giving accurate results.
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Rathi, P., Keni, P., Sisodia, J. (2022). Project Topic Recommendation by Analyzing User’s Interest Using Intelligent Conversational System. In: Raj, J.S., Kamel, K., Lafata, P. (eds) Innovative Data Communication Technologies and Application. Lecture Notes on Data Engineering and Communications Technologies, vol 96. Springer, Singapore. https://doi.org/10.1007/978-981-16-7167-8_21
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DOI: https://doi.org/10.1007/978-981-16-7167-8_21
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