Search results
Results From The WOW.Com Content Network
A vector database, vector store or vector search engine is a database that can store vectors (fixed-length lists of numbers) along with other data items. Vector databases typically implement one or more Approximate Nearest Neighbor algorithms, [1] [2] [3] so that one can search the database with a query vector to retrieve the closest matching database records.
A search string can be specified as one of the query parameters to retrieve matching documents. Azure Search supports search strings using simple query syntax. [6] Supported features include logical operators, the suffix operator, and query with Lucene query syntax. [7] (currently in preview) As an example, white+house
Some authors regard semantic search as a set of techniques for retrieving knowledge from richly structured data sources like ontologies and XML as found on the Semantic Web. [2] Such technologies enable the formal articulation of domain knowledge at a high level of expressiveness and could enable the user to specify their intent in more detail ...
Generating or maintaining a large-scale search engine index represents a significant storage and processing challenge. Many search engines utilize a form of compression to reduce the size of the indices on disk. [19] Consider the following scenario for a full text, Internet search engine. It takes 8 bits (or 1 byte) to store a single character.
Candidate documents from the corpus can be retrieved and ranked using a variety of methods. Relevance rankings of documents in a keyword search can be calculated, using the assumptions of document similarities theory, by comparing the deviation of angles between each document vector and the original query vector where the query is represented as a vector with same dimension as the vectors that ...
On July 18, 2023, the company announced a partnership with Google to make semantic search available in its Astra DB cloud database for developers building generative AI applications. [20] On September 13, 2023, DataStax launched the LangStream open source project, which works with Astra DB and supports vector databases including Milvus and ...
Semantic queries work on named graphs, linked data or triples. This enables the query to process the actual relationships between information and infer the answers from the network of data. This is in contrast to semantic search, which uses semantics (meaning of language constructs) in unstructured text to produce a
MarkLogic was originally named Cerisent when it was founded in 2001 [5] by Christopher Lindblad, who was the Chief Architect of the Ultraseek search engine at Infoseek, as well as Paul Pedersen, a professor of computer science at Cornell University and UCLA, and Frank R. Caufield, Founder of Darwin Ventures, [6] to address shortcomings with existing search and data products.