QUERY PROCESSING COMPONENT OF THE INTELLIGENT REPOSITORY SYSTEM SEARCH ENGINE
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 proc...
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Main Author: | |
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Format: | Final Project |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/73919 |
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Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Summary: | 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. |
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