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In knowledge representation and reasoning, a knowledge graph is a knowledge base that uses a graph-structured data model or topology to represent and operate on data. Knowledge graphs are often used to store interlinked descriptions of entities – objects, events, situations or abstract concepts – while also encoding the free-form semantics ...
With the newer, NoSQL databases and especially with RDF databases (see Triplestore) the storage distinction may no longer apply. Data and models can be stored using the same approach. However, models continue to be more permanent, have a different lifecycle and are typically stored as separate graphs within such database.
Despite the graph databases' advantages and recent popularity over [citation needed] relational databases, it is recommended the graph model itself should not be the sole reason to replace an existing relational database. A graph database may become relevant if there is an evidence for performance improvement by orders of magnitude and lower ...
In representation learning, knowledge graph embedding (KGE), also referred to as knowledge representation learning (KRL), or multi-relation learning, [1] is a machine learning task of learning a low-dimensional representation of a knowledge graph's entities and relations while preserving their semantic meaning.
The Google Knowledge Graph is a knowledge base from which Google serves relevant information in an infobox beside its search results. This allows the user to see the answer in a glance, as an instant answer. The data is generated automatically from a variety of sources, covering places, people, businesses, and more. [1] [2]
Google's Knowledge Graph is powered in part by Freebase. [5] During its existence, Freebase data was available for commercial and non-commercial use under a Creative Commons Attribution License, and an open API, RDF endpoint, and a database dump is provided for programmers.
A personal knowledge base (PKB) is an electronic tool used by an individual to express, capture, and later retrieve personal knowledge.It differs from a traditional database in that it contains subjective material particular to the owner, that others may not agree with nor care about.
This is often used as a form of knowledge representation. It is a directed or undirected graph consisting of vertices, which represent concepts, and edges, which represent semantic relations between concepts, [1] mapping or connecting semantic fields. A semantic network may be instantiated as, for example, a graph database or a concept map.