Published Paper Details:

This study seeks to create a smart system that offers farmers up-to-date and precise information to improve their farming methods and decision-making. By employing Natural Language Processing (NLP) methods, the chatbot analyzes user questions and provides appropriate answers from a set of agricultural knowledge resources. We employed the Natural Language Toolkit (NLTK) for text manipulation and the Term Frequency Inverse Document Frequency (TFIDF) vectorizer to convert text into numerical data. Cosine similarity is then applied to compare user questions with sentences in the knowledge base, ensuring the most pertinent information is retrieved. The entire development process includes several essential steps such as Data Collection, Data Preprocessing, Encoding, Obtaining Response, TFIDF, Cosine Similarity, and Generating Responses for the chatbot to display to users. This system empowers farmers by providing them with convenient access to crucial agricultural information, thereby aiding their efforts to boost productivity and sustainability. By incorporating sophisticated NLP methods, the system improves the accessibility and relevance of agricultural knowledge, leading to the overall empowerment and advancement of the agricultural community. The results show the chatbot's effectiveness in providing accurate and relevant agricultural information, significantly enhancing the farmers' decision-making process and resulting in improved agricultural results.