An overview of semantic search, knowledge graphs & vector databases
Coupled with an overview of performing semantic search on your own private data
What is Semantic search?
Semantic search is a search technique that uses natural language processing algorithms to understand the meaning and context of words and phrases in order to provide more accurate search results. This approach is based on the idea that search engines should not just match keywords in a query, but also try to understand the intent of the user’s search and the relationships between the words used.
Semantic search aims to go beyond traditional keyword-based search algorithms by using techniques such as entity recognition, concept matching, and semantic analysis to identify relationships between words, phrases, and concepts. It also takes into account synonyms, related terms, and context to provide more relevant search results.
Overall, semantic search is designed to provide more precise and meaningful search results that better reflect the user’s intent, rather than just matching keywords. This makes it particularly useful for complex queries, such as those related to scientific research, medical information, or legal documents.
