What is meant by Semantic search?
The term "semantic search" refers to a search technology that aims to understand the meaning of words and contexts to deliver more precise and relevant search results. Unlike traditional keyword-based search, which relies on exact matches, semantic search interprets the intent and context of the query to find content that truly matches the sought information. This is achieved through Natural Language Processing (NLP), machine learning, and ontological models.
Typical software functions in the area of "semantic search":
- Language Understanding: Interpreting and processing natural language to grasp the intent behind search queries and provide the most relevant results.
- Contextualization: Considering the context of the search query, including user history and specific requirements, to achieve more accurate search results.
- Synonym and Concept Recognition: Identifying and processing synonyms, related terms, and concepts to enhance the relevance of search results.
- Advanced Search: Using ontologies and knowledge graphs to link the search query with related topics and concepts.
- Ranking and Relevance Assessment: Evaluating and prioritizing search results based on their relevance to the query and context.
- Feedback Mechanisms: Integrating user feedback to continuously improve search accuracy and relevance.