The evolution of search engines from simple keyword-based systems to more sophisticated semantic-based models marks a significant advancement in the field of information retrieval. This monograph presents a comprehensive study on the development of a Semantic-Based Pattern Search Engine, designed to enhance the accuracy and relevance of search results by understanding the contextual and semantic relationships within data. The research encompasses the creation of various engines, including a concept search engine, topic search engine, affective term detection engine, and emotion prediction engine. Additionally, the application of these technologies in online opinion mining is explored, demonstrating their practical value. The findings of this research contribute to the broader understanding of semantic search and offer valuable insights for future advancements in the domain.

Keywords: Semantic-Based Pattern Search Engine, Concept Search Engine, Topic Search Engine, Affective Term Detection, Emotion Prediction, Online Opinion Mining, Information Retrieval, Semantic Search, Contextual Search

How to Cite:

Ajitha, P. (2024). SEMANTIC BASED PATTERN SEARCH ENGINE (1st ed.). Jupiter Publications Consortium. ISBN: 978-93-86388-47-6, DOI: www.doi.org/10.47715/978-93-86388-47-6