Survey of Swarm Intelligence Approaches to Search Documents Based On Semantic Similarity
Chandrashekar Muniyappa, Eunjin Kim
TL;DR
This survey reviews recent swarm intelligence algorithms used for searching documents based on semantic similarity, highlighting their effectiveness and suggesting future research directions.
Contribution
It provides a comprehensive overview of the latest swarm intelligence methods applied to semantic document search and discusses potential future research avenues.
Findings
Swarm algorithms are effective in semantic document search.
Recent developments enhance search accuracy and efficiency.
Future research should explore hybrid approaches.
Abstract
Swarm Intelligence (SI) is gaining a lot of popularity in artificial intelligence, where the natural behavior of animals and insects is observed and translated into computer algorithms called swarm computing to solve real-world problems. Due to their effectiveness, they are applied in solving various computer optimization problems. This survey will review all the latest developments in Searching for documents based on semantic similarity using Swarm Intelligence algorithms and recommend future research directions.
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