Semantic Search
Search based on meaning and context rather than exact keyword matches
Overview
Semantic search is a search technique that focuses on understanding the meaning and intent of the search query rather than just matching keywords. Semantic search leverages AI and NLP to retrieve more accurate and contextually relevant results, as opposed to keywords-based methods.
Understanding Semantic Search
The system processes queries by:
- Analyzing the meaning behind search terms
- Understanding contextual relationships
- Considering synonyms and related concepts
- Evaluating user intent
- Ranking results by relevance
- Learning from user interactions
Healthcare Applications
In medical contexts, semantic search could help with:
- Finding relevant medical literature
- Accessing patient records efficiently
- Identifying similar case histories
- Locating clinical guidelines
- Suggesting relevant treatment protocols
- Supporting clinical research
Technical Components
Key elements of semantic search include:
- Natural language processing systems
- Vector databases for efficient retrieval
- Relevance ranking algorithms
- Query understanding models
- Content indexing systems
- User feedback integration