QUERY PROCESSING COMPONENT OF THE INTELLIGENT REPOSITORY SYSTEM SEARCH ENGINE - Salsabiila, Shifa
Search engines play a crucial role in today's digital information era by retrieving and presenting relevant information to users based on their query requests. The query processing component is a critical element of search engines as it is responsible for translating, understanding, and processing user input queries to generate accurate and relevant search results. However, search engines commonly face challenges such as receiving user queries that do not accurately represent the search intent and the contextual variations in query meanings. This research focuses on analyzing and designing an effective query processing component for search engines capable of handling diverse domain cases within a document corpus. The proposed query component leverages semantic search concepts by mapping document texts and queries into a vector space. This mapping process is facilitated by a language model trained on a specific dataset containing domain-specific documents. The evaluation of the system demonstrates promising performance in terms of effectiveness and efficiency. The results of this study contribute to the advancement of search engine technology by addressing the challenges associated with query processing and improving the accuracy and relevance of search results. By developing a query processing component that can handle varied domain cases, the research enhances the ability of search engines to deliver optimal outcomes for users.