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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.
Swoogle was a search engine for Semantic Web ontologies, documents, terms and data published on the Web. Swoogle employed a system of crawlers to discover RDF documents and HTML documents with embedded RDF content. Swoogle reasoned about these documents and their constituent parts (e.g., terms and triples) and recorded and indexed meaningful ...
When Pinecone announced a vector database at the beginning of last year, it was building something that was specifically designed for machine learning and aimed at data scientists.
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 ...
Schema.org is a reference website that publishes documentation and guidelines for using structured data mark-up on web-pages (in the form of microdata, RDFa or JSON-LD).Its main objective is to standardize HTML tags to be used by webmasters for creating rich results (displayed as visual data or infographic tables on search engine results) about a certain topic of interest. [2]
Evi (formerly True Knowledge) is a technology company in Cambridge, England, founded by William Tunstall-Pedoe, [1] [2] [3] which specialises in knowledge base and semantic search engine software. Its first product was an answer engine that aimed to directly answer questions on any subject posed in plain English text, which is accomplished ...
Contextual search is a form of optimizing web-based search results based on context provided by the user and the computer being used to enter the query. [1] Contextual search services differ from current search engines based on traditional information retrieval that return lists of documents based on their relevance to the query.
Semantic networks are used by RetrievalWare to expand the query words entered by the user to related terms with terms weights determined by the distance from the user's original terms. In addition to automatic expansion, a feedback-mode whereby users could choose the meaning of the word before performing the expansion was available.