Cwm (software)
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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 RDF, extended to include rules, it can use RDF/XML or RDF/ 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 from 2000–10 onwards by Tim Berners-Lee and Dan Connolly of the W3C The World Wide Web Consortium (W3C) is the main international standards organization ...
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Semantic Web
The Semantic Web, sometimes known as Web 3.0, is an extension of the World Wide Web through standards set by the World Wide Web Consortium (W3C). The goal of the Semantic Web is to make Internet data machine-readable. To enable the encoding of semantics with the data, technologies such as Resource Description Framework (RDF) and Web Ontology Language (OWL) are used. These technologies are used to formally represent metadata. For example, Ontology (information science), ontology can describe concepts, relationships between Entity–relationship model, entities, and categories of things. These embedded semantics offer significant advantages such as reasoning engine, reasoning over data and operating with heterogeneous data sources. These standards promote common data formats and exchange protocols on the Web, fundamentally the RDF. According to the W3C, "The Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and commu ...
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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. These formats can be subsequently converted to 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. 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. The XSLT document transformation specifies how to transform an XML document into new document (usually XML, but other formats, such as plain text are supported). Typically, input documents are XML files, but anything from which the processor can build an XQuery and XPath Data Model can be used, such as relational database tables or geographical inform ...
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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 ...
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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 ...
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Resource Description Framework
The Resource Description Framework (RDF) is a method to describe and exchange graph data. It was originally designed as a data model for metadata by the World Wide Web Consortium (W3C). It provides a variety of syntax notations and formats, of which the most widely used is Turtle ( Terse RDF Triple Language). 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 from subject to object, representing a predicate, and (3) a node for the object. Each of these parts can be identified by a Uniform Resource Identifier (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, and the RDF 1.1 specification in 2014. SPARQL is a standard query ...
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Rule Of Inference
Rules of inference are ways of deriving conclusions from premises. They are integral parts of formal logic, serving as norms of the Logical form, logical structure of Validity (logic), valid arguments. If an argument with true premises follows a rule of inference then the conclusion cannot be false. ''Modus ponens'', an influential rule of inference, connects two premises of the form "if P then Q" and "P" to the conclusion "Q", as in the argument "If it rains, then the ground is wet. It rains. Therefore, the ground is wet." There are many other rules of inference for different patterns of valid arguments, such as ''modus tollens'', disjunctive syllogism, constructive dilemma, and existential generalization. Rules of inference include rules of implication, which operate only in one direction from premises to conclusions, and rules of replacement, which state that two expressions are equivalent and can be freely swapped. Rules of inference contrast with formal fallaciesinvalid argu ...
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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
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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 suit ...
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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" (i.e., Bob's age measured in years 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 the 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 ...
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Inference
Inferences are steps in logical 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 BC). 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. Statist ...
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FOPL
First-order logic, also called predicate logic, predicate calculus, or quantificational logic, is a collection of formal systems used in mathematics, philosophy, linguistics, and computer science. First-order logic uses quantified variables over non-logical objects, and allows the use of sentences that contain variables. Rather than propositions such as "all humans are mortal", in first-order logic one can have expressions in the form "for all ''x'', if ''x'' is a human, then ''x'' is mortal", where "for all ''x"'' is a quantifier, ''x'' is a variable, and "... ''is a human''" and "... ''is mortal''" are predicates. This distinguishes it from propositional logic, which does not use quantifiers or relations; in this sense, propositional logic is the foundation of first-order logic. A theory about a topic, such as set theory, a theory for groups,A. Tarski, ''Undecidable Theories'' (1953), p. 77. Studies in Logic and the Foundation of Mathematics, North-Holland or a formal theory of ...
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Inference Engine
In the field of artificial intelligence, an inference engine is a software component of an intelligent 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 applied 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. Additionally, the concept of 'inference' has expanded to include the process t ...
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