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Cwm (software)
{{distinguish, cwm (window manager) Cwm (pronounced koom) is a general-purpose data processing software for the Semantic Web, similar to sed or awk for text files or XSLT for XML. It is a forward chaining semantic reasoner that can be used for querying, checking, transforming and filtering information. Its core language is Resource Description Framework, RDF, extended to include Rule of inference, rules, it can use Resource Description Framework, RDF/XML or RDF/Notation3, N3 (seNotation3 Primer serializations. cwm can perform the following tasks: * Parse and pretty-print the following RDF formats: XML RDF, Notation3, and N-Triples. * Store triples in a queryable triplestore (a triples database). * Perform inferences as a forward chaining FOPL inference engine. * Perform builtin functions such as comparing strings, retrieving resources, all using an extensible builtins suite. cwm was written in Python (programming language), Python from 2000-10 onwards by Tim Berners-Lee and Dan C ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
XSLT
XSLT (Extensible Stylesheet Language Transformations) is a language originally designed for transforming XML documents into other XML documents, or other formats such as HTML for web pages, plain text or XSL Formatting Objects, which may subsequently be converted to other formats, such as PDF, PostScript and PNG. Support for JSON and plain-text transformation was added in later updates to the XSLT 1.0 specification. As of August 2022, the most recent stable version of the language is XSLT 3.0, which achieved Recommendation status in June 2017. XSLT 3.0 implementations support Java, .NET, C/C++, Python, PHP and NodeJS. An XSLT 3.0 Javascript library can also be hosted within the Web Browser. Modern web browsers also include native support for XSLT 1.0. For an XSLT document transformation, the original document is not changed; rather, a new document is created based on the content of an existing one. Typically, input documents are XML files, but anything from which the processo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Forward Chaining
Forward chaining (or forward reasoning) is one of the two main methods of reasoning when using an inference engine and can be described logically as repeated application of ''modus ponens''. Forward chaining is a popular implementation strategy for expert systems, business and production rule systems. The opposite of forward chaining is backward chaining. Forward chaining starts with the available data and uses inference rules to extract more data (from an end user, for example) until a goal is reached. An inference engine using forward chaining searches the inference rules until it finds one where the antecedent (If clause) is known to be true. When such a rule is found, the engine can conclude, or infer, the consequent (Then clause), resulting in the addition of new information to its data. Inference engines will iterate through this process until a goal is reached. Example Suppose that the goal is to conclude the color of a pet named Fritz, given that he croaks and eats ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Resource Description Framework
The Resource Description Framework (RDF) is a World Wide Web Consortium (W3C) standard originally designed as a data model for metadata. It has come to be used as a general method for description and exchange of graph data. RDF provides a variety of syntax notations and data serialization formats with Turtle (Terse RDF Triple Language) currently being the most widely used notation. RDF is a directed graph composed of triple statements. An RDF graph statement is represented by: 1) a node for the subject, 2) an arc that goes from a subject to an object for the predicate, and 3) a node for the object. Each of the three parts of the statement can be identified by a URI. An object can also be a literal value. This simple, flexible data model has a lot of expressive power to represent complex situations, relationships, and other things of interest, while also being appropriately abstract. RDF was adopted as a W3C recommendation in 1999. The RDF 1.0 specification was published in 2004, th ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Rule Of Inference
In the philosophy of logic, a rule of inference, inference rule or transformation rule is a logical form consisting of a function which takes premises, analyzes their syntax, and returns a conclusion (or conclusions). For example, the rule of inference called ''modus ponens'' takes two premises, one in the form "If p then q" and another in the form "p", and returns the conclusion "q". The rule is valid with respect to the semantics of classical logic (as well as the semantics of many other non-classical logics), in the sense that if the premises are true (under an interpretation), then so is the conclusion. Typically, a rule of inference preserves truth, a semantic property. In many-valued logic, it preserves a general designation. But a rule of inference's action is purely syntactic, and does not need to preserve any semantic property: any function from sets of formulae to formulae counts as a rule of inference. Usually only rules that are recursive are important; i.e. rules suc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Notation3
Notation3, or N3 as it is more commonly known, is a shorthand non-XML serialization of Resource Description Framework models, designed with human-readability in mind: N3 is much more compact and readable than XML RDF notation. The format is being developed by Tim Berners-Lee and others from the Semantic Web community. A formalization of the logic underlying N3 was published by Berners-Lee and others in 2008. N3 has several features that go beyond a serialization for RDF models, such as support for RDF-based rules. Turtle is a simplified, RDF-only subset of N3. Examples The following is an RDF model in standard XML notation: Tony Benn Wikipedia may be written in Notation3 like this: @prefix dc: . dc:title "Tony Benn"; dc:publisher "Wikipedia". This N3 code above would also be in valid Turtle syntax. Comparison of Notation3, Turtle, and N-Triples See also * N-Triples * Turtle (syntax) External linksNotation 3 W3C Submission [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
N-Triples
N-Triples is a format for storing and transmitting data. It is a line-based, plain text serialisation format for RDF (Resource Description Framework) graphs, and a subset of the Turtle (Terse RDF Triple Language) format. N-Triples should not be confused with Notation3 which is a superset of Turtle. N-Triples was primarily developed by Dave Beckett at the University of Bristol and Art Barstow at the World Wide Web Consortium (W3C). N-Triples was designed to be a simpler format than Notation3 and Turtle, and therefore easier for software to parse and generate. However, because it lacks some of the shortcuts provided by other RDF serialisations (such as CURIEs and nested resources, which are provided by both RDF/XML and Turtle) it can be onerous to type out large amounts of data by hand, and difficult to read. Usage There is very little variation in how an RDF graph can be represented in N-Triples. This makes it a very convenient format to provide "model answers" foRDF test suites ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Triplestore
A triplestore or RDF store is a purpose-built database for the storage and retrieval of triples through semantic queries. A triple is a data entity composed of subject–predicate–object, like "Bob is 35" or "Bob knows Fred". Much like a relational database, information in a triplestore is stored and retrieved via a query language. Unlike a relational database, a triplestore is optimized for the storage and retrieval of triples. In addition to queries, triples can usually be imported and exported using Resource Description Framework (RDF) and other formats. Implementations Some triplestores have been built as database engines from scratch, while others have been built on top of existing commercial relational database engines (such as SQL-based) or NoSQL document-oriented database engines. Like the early development of online analytical processing (OLAP) databases, this intermediate approach allowed large and powerful database engines to be constructed for little programming ef ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Inference
Inferences are steps in reasoning, moving from premises to logical consequences; etymologically, the word '' infer'' means to "carry forward". Inference is theoretically traditionally divided into deduction and induction, a distinction that in Europe dates at least to Aristotle (300s BCE). Deduction is inference deriving logical conclusions from premises known or assumed to be true, with the laws of valid inference being studied in logic. Induction is inference from particular evidence to a universal conclusion. A third type of inference is sometimes distinguished, notably by Charles Sanders Peirce, contradistinguishing abduction from induction. Various fields study how inference is done in practice. Human inference (i.e. how humans draw conclusions) is traditionally studied within the fields of logic, argumentation studies, and cognitive psychology; artificial intelligence researchers develop automated inference systems to emulate human inference. Statistical inference ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Inference Engine
In the field of artificial intelligence, an inference engine is a component of the system that applies logical rules to the knowledge base to deduce new information. The first inference engines were components of expert systems. The typical expert system consisted of a knowledge base and an inference engine. The knowledge base stored facts about the world. The inference engine applies logical rules to the knowledge base and deduced new knowledge. This process would iterate as each new fact in the knowledge base could trigger additional rules in the inference engine. Inference engines work primarily in one of two modes either special rule or facts: forward chaining and backward chaining. Forward chaining starts with the known facts and asserts new facts. Backward chaining starts with goals, and works backward to determine what facts must be asserted so that the goals can be achieved. Architecture The logic that an inference engine uses is typically represented as IF-THEN rules. The ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |