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Knowledge Discovery
Knowledge extraction is the creation of knowledge from structured ( relational databases, XML) and unstructured (text, documents, images) sources. The resulting knowledge needs to be in a machine-readable and machine-interpretable format and must represent knowledge in a manner that facilitates inferencing. Although it is methodically similar to information extraction ( NLP) and ETL (data warehouse), the main criterion is that the extraction result goes beyond the creation of structured information or the transformation into a relational schema. It requires either the reuse of existing formal knowledge (reusing identifiers or ontologies) or the generation of a schema based on the source data. The RDB2RDF W3C group is currently standardizing a language for extraction of resource description frameworks (RDF) from relational databases. Another popular example for knowledge extraction is the transformation of Wikipedia into structured data and also the mapping to existing knowl ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Knowledge Representation And Reasoning
Knowledge representation (KR) aims to model information in a structured manner to formally represent it as knowledge in knowledge-based systems whereas knowledge representation and reasoning (KRR, KR&R, or KR²) also aims to understand, reason, and interpret knowledge. KRR is widely used in the field of artificial intelligence (AI) with the goal to represent information about the world in a form that a computer system can use to solve complex tasks, such as diagnosing a medical condition or having a natural-language dialog. KR incorporates findings from psychology about how humans solve problems and represent knowledge, in order to design formalisms that make complex systems easier to design and build. KRR also incorporates findings from logic to automate various kinds of ''reasoning''. Traditional KRR focuses more on the declarative representation of knowledge. Related knowledge representation formalisms mainly include vocabularies, thesaurus, semantic networks, axiom system ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
DBpedia Spotlight
DBpedia (from "DB" for "database") is a project aiming to extract structured content from the information created in the Wikipedia project. This structured information is made available on the World Wide Web using OpenLink Virtuoso. DBpedia allows users to semantically query relationships and properties of Wikipedia resources, including links to other related datasets. The project was heralded as "one of the more famous pieces" of the decentralized Linked Data effort by Tim Berners-Lee, one of the Web's pioneers. As of June 2021, DBPedia contained over 850 million triples. Background The project was started by people at the Free University of Berlin and Leipzig University''DBpedia: A Nucleus for a Web of Open Data'', available a in collaboration with OpenLink Software, and is now maintained by people at the University of Mannheim and Leipzig University. The first publicly available dataset was published in 2007. The data is made available under free licenses (CC BY-SA), all ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Tim Berners-Lee
Sir Timothy John Berners-Lee (born 8 June 1955), also known as TimBL, is an English computer scientist best known as the inventor of the World Wide Web, the HTML markup language, the URL system, and HTTP. He is a professorial research fellow at the University of Oxford and a professor emeritus at the Massachusetts Institute of Technology (MIT). Berners-Lee proposed an information management system on 12 March 1989 and implemented the first successful communication between a Hypertext Transfer Protocol (HTTP) client and Server (computing), server via the Internet in mid-November. He devised and implemented the first Web browser and Web server and helped foster the Web's subsequent development. He is the founder and emeritus director of the World Wide Web Consortium (W3C), which oversees the continued development of the Web. He co-founded (with Rosemary Leith) the World Wide Web Foundation. In April 2009, he was elected as Foreign Associate of the National Academy of Sciences. B ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Domain Knowledge
Domain knowledge is knowledge of a specific discipline or field in contrast to general (or domain-independent) knowledge. The term is often used in reference to a more general discipline—for example, in describing a software engineer who has general knowledge of computer programming as well as domain knowledge about developing programs for a particular industry. People with domain knowledge are often regarded as specialists or experts in their field. Knowledge capture In software engineering, ''domain knowledge'' is knowledge about the environment in which the target system operates, for example, software agents. Domain knowledge usually must be learned from software users in the domain (as domain specialists/experts), rather than from software developers. It may include user workflows, data pipelines, business policies, configurations and constraints and is crucial in the development of a software application. Expert domain knowledge (frequently informal and ill-structured) is ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Ontology (information Science)
In information science, an ontology encompasses a representation, formal naming, and definitions of the categories, properties, and relations between the concepts, data, or entities that pertain to one, many, or all domains of discourse. More simply, an ontology is a way of showing the properties of a subject area and how they are related, by defining a set of terms and relational expressions that represent the entities in that subject area. The field which studies ontologies so conceived is sometimes referred to as ''applied ontology''. Every academic discipline or field, in creating its terminology, thereby lays the groundwork for an ontology. Each uses ontological assumptions to frame explicit theories, research and applications. Improved ontologies may improve problem solving within that domain, interoperability of data systems, and discoverability of data. Translating research papers within every field is a problem made easier when experts from different countries mainta ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Virtuoso Universal Server
Virtuoso Universal Server is a middleware and database engine hybrid that combines the functionality of a traditional relational database management system (RDBMS), object–relational database (ORDBMS), virtual database, RDF, XML, free-text, web application server and file server functionality in a single system. Rather than have dedicated servers for each of the aforementioned functionality realms, Virtuoso is a "universal server"; it enables a single multithreaded server process that implements multiple protocols. The free and open source edition of Virtuoso Universal Server is also known as OpenLink Virtuoso. The software has been developed by OpenLink Software with Kingsley Uyi Idehen and Orri Erling as the chief software architects. Database structure Core database engine Virtuoso provides an extended object–relational model, which combines the flexibility of relational access with inheritance, run time data typing, late binding, and identity-based access. V ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
YAGO (Ontology)
YAGO (Yet Another Great Ontology) is an open source knowledge base developed at the Max Planck Institute for Informatics in Saarbrücken. It is automatically extracted from Wikidata and Schema.org. YAGO4, which was released in 2020, combines data that was extracted from Wikidata with relationship designators from Schema.org. The previous version of YAGO, YAGO3, had knowledge of more than 10 million entities and contained more than 120 million facts about these entities. The information in YAGO3 was extracted from Wikipedia (e.g., categories, redirects, infoboxes), WordNet (e.g., synsets, hyponymy), and GeoNames. The accuracy of YAGO was manually evaluated to be above 95% on a sample of facts. To integrate it to the linked data cloud, YAGO has been linked to the DBpedia ontology and to the SUMO ontology. YAGO3 is provided in Turtle and tsv formats. Dumps of the whole database are available, as well as thematic and specialized dumps. It can also be queried through various online ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
FOAF (software)
FOAF (an acronym of friend of a friend) is a machine-readable data, machine-readable ontology (information science), ontology describing persons, their activities and their relations to other people and objects. Anyone can use FOAF to describe themselves. FOAF allows groups of people to describe social networks without the need for a centralised database. FOAF is a descriptive vocabulary expressed using the Resource Description Framework (RDF) and the Web Ontology Language (OWL). Computers may use these FOAF profiles to find, for example, all people living in Europe, or to list all people both you and a friend of yours know. This is accomplished by defining relationships between people. Each profile has a unique identifier (such as the person's e-mail addresses, international telephone number, Facebook account name, a Extensible Messaging and Presence Protocol, Jabber ID, or a Uniform Resource Identifier, URI of the homepage or weblog of the person), which is used when defining th ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Semantic Reasoner
A semantic reasoner, reasoning engine, rules engine, or simply a reasoner, is a piece of software able to infer logical consequences from a set of asserted facts or axioms. The notion of a semantic reasoner generalizes that of an inference engine, by providing a richer set of mechanisms to work with. The inference rules are commonly specified by means of an ontology language, and often a description logic language. Many reasoners use first-order predicate logic to perform reasoning; inference commonly proceeds by forward chaining and backward chaining. There are also examples of probabilistic reasoners, including non-axiomatic reasoning systems, and probabilistic logic networks. Notable applications Notable semantic reasoners and related software: Free to use (closed source) * Cyc inference engine, a forward and backward chaining inference engine with numerous specialized modules for high-order logic. * KAON2 is an infrastructure for managing OWL-DL, SWRL, and F-L ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
LinkedData
In computing, linked data is structured data which is interlinked with other data so it becomes more useful through semantic queries. It builds upon standard Web technologies such as HTTP, RDF and URIs, but rather than using them to serve web pages only for human readers, it extends them to share information in a way that can be read automatically by computers. Part of the vision of linked data is for the Internet to become a global database. Tim Berners-Lee, director of the World Wide Web Consortium (W3C), coined the term in a 2006 design note about the Semantic Web project. Linked data may also be open data, in which case it is usually described as Linked Open Data. Principles In his 2006 "Linked Data" note, Tim Berners-Lee outlined four principles of linked data, paraphrased along the following lines: #Uniform Resource Identifiers (URIs) should be used to name and identify individual things. #HTTP URIs should be used to allow these things to be looked up, interpreted, and ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
