An Analysis of the Technical Trend of Semantic Search in Natural Language Processing

Semantic search is an important task in Natural language processing (NLP). It aims to improve the accuracy of search results by understanding the meaning of search queries. This paper introduces the basic concepts, development history, and application status of semantic search in different fields, and explains the current challenges of semantic search, such as polysemy and ambiguity problems, semantic understanding and semantic modeling.This paper mainly describes the main natural language processing technologies in semantic search, including deep learning-based methods, text representation, intent recognition, relationship extraction, and machine learning. Finally, this paper discusses the trends and prospects of semantic search development in the future.