Semantic Search
Fri, 19 Aug 2022 09:13:49 GMT — Properties
Properties
| Key | Value |
|---|---|
| Identifier | semantic-search |
| Name | Semantic Search |
| Type | Topic |
| Creation timestamp | Fri, 19 Aug 2022 09:13:49 GMT |
| Modification timestamp | Fri, 19 Aug 2022 09:52:05 GMT |
Embeddings
Backed by machine learning models, data is transformed into vector representations for search (also known as embeddings). Stated differently, embeddings is the engine that delivers semantic search. Data is transformed into embeddings vectors where similar concepts will produce similar vectors. Indexes are built with these vectors. The indexes are used to find results that have the same meaning, not necessarily the same keywords.
Topic location
- Map: Knowledge Graphs — Info
- Topic: Semantic Search
- Scope: Universal Active
Topic resources
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