Using Proximity and Semantic Similarity in Question Answering - Phaldessai, Shaunak S; Kerkar, Amey DS (International Journal of Computer Sciences and Engineering, 2025)
This paper deals with the process of Question Answering, using news articles crawled from ‘THE HINDU’ newspaper website of the year 2017. We make use of corpus of close to 10,000 articles/documents crawled categorically into Sports, Science and Tech., Business and Entertainment. We have implemented a system that extracts documents based on relevance to the question a user asks through the tf-idf ranking. For the processing phase, we made use of methods initially implemented for simpler systems, such as document extraction and checking sentence similarity between two short sentences. We managed to implement the techniques to extract coherent answers by extracting the passages with the best likelihood of containing the answer and the process these passages for the answer based on their similarity with the question. To implement these, we have made use of various Natural Language Processing (NLP) techniques along with the Wordnet knowledge base. We have tested the system with different corpus sizes and different coefficient of cosine similarity to explore this technique.