Deductive Database
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Deductive Database
A deductive database is a database system that can make deductions (i.e. conclude additional facts) based on rules and facts stored in the (deductive) database. Datalog is the language typically used to specify facts, rules and queries in deductive databases. Deductive databases have grown out of the desire to combine logic programming with relational databases to construct systems that support a powerful formalism and are still fast and able to deal with very large datasets. Deductive databases are more expressive than relational databases but less expressive than logic programming systems. In recent years, deductive databases such as Datalog have found new application in data integration, information extraction, networking, program analysis, security, and cloud computing. Deductive databases reuse many concepts from logic programming; rules and facts specified in the deductive database language Datalog look very similar to those in Prolog. However important differences between ...
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Database System
In computing, a database is an organized collection of data stored and accessed electronically. Small databases can be stored on a file system, while large databases are hosted on computer clusters or cloud storage. The design of databases spans formal techniques and practical considerations, including data modeling, efficient data representation and storage, query languages, security and privacy of sensitive data, and distributed computing issues, including supporting concurrent access and fault tolerance. A database management system (DBMS) is the software that interacts with end users, applications, and the database itself to capture and analyze the data. The DBMS software additionally encompasses the core facilities provided to administer the database. The sum total of the database, the DBMS and the associated applications can be referred to as a database system. Often the term "database" is also used loosely to refer to any of the DBMS, the database system or an application ...
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Program Analysis
In computer science, program analysis is the process of automatically analyzing the behavior of computer programs regarding a property such as correctness, robustness, safety and liveness. Program analysis focuses on two major areas: program optimization and program correctness. The first focuses on improving the program’s performance while reducing the resource usage while the latter focuses on ensuring that the program does what it is supposed to do. Program analysis can be performed without executing the program (static program analysis), during runtime (dynamic program analysis) or in a combination of both. Static program analysis In the context of program correctness, static analysis can discover vulnerabilities during the development phase of the program.Jovanovic, N., Kruegel, C., & Kirda, E. (2006, May). Pixy: A static analysis tool for detecting web application vulnerabilities. In Security and Privacy, 2006 IEEE Symposium on (pp. 6-pp). IEEE. These vulnerabilities a ...
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Stefano Ceri
Stefano Ceri (born 14 February 1955) is an Italian computer engineering, computer engineer and professor of database management at Politecnico di Milano. He has been visiting professor at Stanford University between 1983 and 1990, and received the Association for Computing Machinery, ACM SIGMOD Edgar F. Codd Innovations Award, SIGMOD Edward Codd Innovations Award in 2013. Career Stanford University He was a visiting professor at Stanford University in the 1980s and 1990s. Scientific Research Some of the research projects he has been responsible of at Politecnico di Milano include W3I3: "''Web-Based Intelligent Information Infrastructures''" (1998–2000), WebSI: "''Data Centric Web Services Integrator''" (2002–2004), SeCoSearch Computing(2008–2013), GenData2020: Data-Centric Genomic Computing (2013–2016), and GeCo: Genomic Computing (2016-2021). He received two European Research Council Advanced Grants, in 2008 for the Search Computing project and in 2016 for the Genomic ...
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Jack Minker
Jack Minker (4 July 1927 – 9 April 2021) was a leading authority in artificial intelligence, deductive databases, logic programming and non-monotonic reasoning. He was also an internationally recognized leader in the field of human rights of computer scientists. He was an Emeritus Professor in the University of Maryland Department of Computer Science, which is part of the College of Computer, Mathematical, and Natural Sciences. Education and early life Minker was born on July 4, 1927 in Brooklyn, New York. He received his Bachelor of Arts degree from Brooklyn College in 1949, Master of Arts degree from the University of Wisconsin in 1950, and PhD from the University of Pennsylvania in 1959 for research supervised by Bernard Epstein. Career and research Minker started his career in industry in 1951, working at the Bell Aircraft Corporation, RCA, and the Auerbach Corporation. He joined the University of Maryland in 1967, becoming Professor of Computer Science in 1971 and the ...
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Tuple
In mathematics, a tuple is a finite ordered list (sequence) of elements. An -tuple is a sequence (or ordered list) of elements, where is a non-negative integer. There is only one 0-tuple, referred to as ''the empty tuple''. An -tuple is defined inductively using the construction of an ordered pair. Mathematicians usually write tuples by listing the elements within parentheses "" and separated by a comma and a space; for example, denotes a 5-tuple. Sometimes other symbols are used to surround the elements, such as square brackets "nbsp; or angle brackets "⟨ ⟩". Braces "" are used to specify arrays in some programming languages but not in mathematical expressions, as they are the standard notation for sets. The term ''tuple'' can often occur when discussing other mathematical objects, such as vectors. In computer science, tuples come in many forms. Most typed functional programming languages implement tuples directly as product types, tightly associated with algebr ...
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Functional Predicate
In formal logic and related branches of mathematics, a functional predicate, or function symbol, is a logical symbol that may be applied to an object term to produce another object term. Functional predicates are also sometimes called mappings, but that term has additional meanings in mathematics. In a model, a function symbol will be modelled by a function. Specifically, the symbol ''F'' in a formal language is a functional symbol if, given any symbol ''X'' representing an object in the language, ''F''(''X'') is again a symbol representing an object in that language. In typed logic, ''F'' is a functional symbol with ''domain'' type T and ''codomain'' type U if, given any symbol ''X'' representing an object of type T, ''F''(''X'') is a symbol representing an object of type U. One can similarly define function symbols of more than one variable, analogous to functions of more than one variable; a function symbol in zero variables is simply a constant symbol. Now consider a model o ...
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Cut (logic Programming)
The cut, in Prolog, is a goal, written as !, which always succeeds, but cannot be backtracked. Cuts can be used to prevent unwanted backtracking, which could add unwanted solutions and/or space/time overhead to a query. The cut should be used sparingly. While cuts can be inserted into codes containing errors, if a test is unnecessary because a cut has guaranteed that it is true, it is good practice to say so in a comment at the appropriate place. Some programmers call the cut a controversial control facility Foundations of Logic Programming', Springer (2012). because it was added for efficiency reasons only and is not a Horn clause. Types Green cut The use of a cut which only improves efficiency is referred to as a green cut. Green cuts are used to make programs more efficient without changing program output. For example: gamble(X) :- gotmoney(X),!. gamble(X) :- gotcredit(X), \+ gotmoney(X). This is called a ' cut operator. The ! tells the interpreter to stop looking for ...
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Prolog
Prolog is a logic programming language associated with artificial intelligence and computational linguistics. Prolog has its roots in first-order logic, a formal logic, and unlike many other programming languages, Prolog is intended primarily as a declarative programming language: the program logic is expressed in terms of relations, represented as facts and rules. A computation is initiated by running a ''query'' over these relations. The language was developed and implemented in Marseille, France, in 1972 by Alain Colmerauer with Philippe Roussel, based on Robert Kowalski's procedural interpretation of Horn clauses at University of Edinburgh. Prolog was one of the first logic programming languages and remains the most popular such language today, with several free and commercial implementations available. The language has been used for theorem proving, expert systems, term rewriting, type systems, and automated planning, as well as its original intended field of use, nat ...
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Information Extraction
Information extraction (IE) is the task of automatically extracting structured information from unstructured and/or semi-structured machine-readable documents and other electronically represented sources. In most of the cases this activity concerns processing human language texts by means of natural language processing (NLP). Recent activities in multimedia document processing like automatic annotation and content extraction out of images/audio/video/documents could be seen as information extraction Due to the difficulty of the problem, current approaches to IE (as of 2010) focus on narrowly restricted domains. An example is the extraction from newswire reports of corporate mergers, such as denoted by the formal relation: :\mathrm(company_1, company_2, date), from an online news sentence such as: :''"Yesterday, New York based Foo Inc. announced their acquisition of Bar Corp."'' A broad goal of IE is to allow computation to be done on the previously unstructured data. A more sp ...
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Deductive Reasoning
Deductive reasoning is the mental process of drawing deductive inferences. An inference is deductively valid if its conclusion follows logically from its premises, i.e. if it is impossible for the premises to be true and the conclusion to be false. For example, the inference from the premises "all men are mortal" and "Socrates is a man" to the conclusion "Socrates is mortal" is deductively valid. An argument is ''sound'' if it is ''valid'' and all its premises are true. Some theorists define deduction in terms of the intentions of the author: they have to intend for the premises to offer deductive support to the conclusion. With the help of this modification, it is possible to distinguish valid from invalid deductive reasoning: it is invalid if the author's belief about the deductive support is false, but even invalid deductive reasoning is a form of deductive reasoning. Psychology is interested in deductive reasoning as a psychological process, i.e. how people ''actually'' draw ...
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Data Integration
Data integration involves combining data residing in different sources and providing users with a unified view of them. This process becomes significant in a variety of situations, which include both commercial (such as when two similar companies need to merge their databases) and scientific (combining research results from different bioinformatics repositories, for example) domains. Data integration appears with increasing frequency as the volume (that is, big data) and the need to share existing data explodes. It has become the focus of extensive theoretical work, and numerous open problems remain unsolved. Data integration encourages collaboration between internal as well as external users. The data being integrated must be received from a heterogeneous database system and transformed to a single coherent data store that provides synchronous data across a network of files for clients. A common use of data integration is in data mining when analyzing and extracting informati ...
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Expressive Power (computer Science)
In computer science, the expressive power (also called expressiveness or expressivity) of a language is the breadth of ideas that can be represented and communicated in that language. The more expressive a language is, the greater the variety and quantity of ideas it can be used to represent. For example, the Web Ontology Language expression language profile (OWL2 EL) lacks ideas (such as negation) which can be expressed in OWL2 RL (rule language). OWL2 EL may therefore be said to have less ''expressive power'' than OWL2 RL. These restrictions allow for more efficient (polynomial time) reasoning in OWL2 EL than in OWL2 RL. So OWL2 EL trades some expressive power for more efficient reasoning (processing of the knowledge representation language). Information description The term ''expressive power'' may be used with a range of meaning. It may mean a measure of the ideas expressible in that language: * regardless of ease (''theoretical expressivity'') * concisely and readily ...
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