Abstract
This paper gives a complete study on the creation of an Assamese question-answering system (AQAS) employing two fundamental methods: cosine similarity and Jaccard similarity. Cosine similarity is a measure of similarity between two vectors, whereas Jaccard similarity is a measure of similarity between two sets. To improve efficiency, the cosine similarity method is paired with non-negative matrix factorization (NMF), which substantially reduces both space and temporal complexity. Our approach gets an accuracy rate of 93.8% for cosine similarity and 87.38% for Jaccard similarity after thorough testing. These results demonstrate the efficiency of our method in providing precise Assamese language responses. This work provides useful insights into the topic of Assamese question-answering systems and their practical applications.
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Baruah, N., Gupta, S., Ghosh, S., Afrid, S.N., Kakoty, C., Phukan, R. (2023). Exploring Jaccard Similarity and Cosine Similarity for Developing an Assamese Question-Answering System. In: Tripathi, A.K., Anand, D., Nagar, A.K. (eds) Proceedings of World Conference on Artificial Intelligence: Advances and Applications. WWCA 1997. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-99-5881-8_8
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