Recherche d'informationLa recherche d'information (RI) est le domaine qui étudie la manière de retrouver des informations dans un corpus. Celui-ci est composé de documents d'une ou plusieurs bases de données, qui sont décrits par un contenu ou les métadonnées associées. Les bases de données peuvent être relationnelles ou non structurées, telles celles mises en réseau par des liens hypertexte comme dans le World Wide Web, l'internet et les intranets. Le contenu des documents peut être du texte, des sons, des images ou des données.
Semantic data modelA semantic data model (SDM) is a high-level semantics-based database description and structuring formalism (database model) for databases. This database model is designed to capture more of the meaning of an application environment than is possible with contemporary database models. An SDM specification describes a database in terms of the kinds of entities that exist in the application environment, the classifications and groupings of those entities, and the structural interconnections among them.
Moteur d'inférenceUn moteur d'inférence (du verbe « inférer » qui signifie « déduire ») est un logiciel (processus informatique) correspondant à un algorithme de simulation des raisonnements déductifs. Un moteur d'inférence permet aux systèmes experts de conduire des raisonnements logiques et de dériver des conclusions à partir d'une base de faits et d'une base de connaissances. Les moteurs d'inférence peuvent implémenter : une logique formelle d'ordre 0 (logique des propositions), d'ordre 0+, d'ordre 1 (logique des prédicats) ou d'ordre 2 avec une gestion d'hypothèses monotone ou non monotone, un chaînage avant, chaînage arrière ou mixte, une complétude déductive ou non.
Relationship extractionA relationship extraction task requires the detection and classification of semantic relationship mentions within a set of artifacts, typically from text or XML documents. The task is very similar to that of information extraction (IE), but IE additionally requires the removal of repeated relations (disambiguation) and generally refers to the extraction of many different relationships. The concept of relationship extraction was first introduced during the 7th Message Understanding Conference in 1998.
Inférence (logique)L’inférence est un mouvement de la pensée qui permet de passer d'une ou plusieurs assertions, des énoncés ou propositions affirmés comme vrais, appelés prémisses, à une nouvelle assertion qui en est la conclusion. Étymologiquement, le mot inférence signifie « reporter ». En théorie, l'inférence est traditionnellement divisée en déduction et induction, une distinction qui, en Europe, remonte au moins à Aristote ( avant Jésus-Christ). On distingue les inférences immédiates des inférences médiates telles que déductives, inductives et abductives.
Schema matchingThe terms schema matching and mapping are often used interchangeably for a database process. For this article, we differentiate the two as follows: schema matching is the process of identifying that two objects are semantically related (scope of this article) while mapping refers to the transformations between the objects. For example, in the two schemas DB1.Student (Name, SSN, Level, Major, Marks) and DB2.Grad-Student (Name, ID, Major, Grades); possible matches would be: DB1.Student ≈ DB2.Grad-Student; DB1.
Capture de données d'écranLa capture de données d’écran (screen scraping en anglais) est une technique par laquelle un programme récupère des données normalement destinées à être affichées par un dispositif de sortie vidéo (généralement un moniteur) afin d’en extraire des informations. Il s’agit souvent de pages web dans lesquelles on souhaite récupérer des informations, mais il peut également s’agir de toute autre forme d’informations qui est formatée avant tout en vue d’être affichée sur un écran.
Knowledge acquisitionKnowledge acquisition is the process used to define the rules and ontologies required for a knowledge-based system. The phrase was first used in conjunction with expert systems to describe the initial tasks associated with developing an expert system, namely finding and interviewing domain experts and capturing their knowledge via rules, objects, and frame-based ontologies. Expert systems were one of the first successful applications of artificial intelligence technology to real world business problems.
Relation (database)In database theory, a relation, as originally defined by E. F. Codd, is a set of tuples (d1, d2, ..., dn), where each element dj is a member of Dj, a data domain. Codd's original definition notwithstanding, and contrary to the usual definition in mathematics, there is no ordering to the elements of the tuples of a relation. Instead, each element is termed an attribute value. An attribute is a name paired with a domain (nowadays more commonly referred to as a type or data type).
Knowledge-based systemsA knowledge-based system (KBS) is a computer program that reasons and uses a knowledge base to solve complex problems. The term is broad and refers to many different kinds of systems. The one common theme that unites all knowledge based systems is an attempt to represent knowledge explicitly and a reasoning system that allows it to derive new knowledge. Thus, a knowledge-based system has two distinguishing features: a knowledge base and an inference engine.
Knowledge representation and reasoningKnowledge representation and reasoning (KRR, KR&R, KR2) is the field of artificial intelligence (AI) dedicated to representing 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 dialog in a natural language. Knowledge representation incorporates findings from psychology about how humans solve problems and represent knowledge in order to design formalisms that will make complex systems easier to design and build.
Logical schemaA logical data model or logical schema is a data model of a specific problem domain expressed independently of a particular database management product or storage technology (physical data model) but in terms of data structures such as relational tables and columns, object-oriented classes, or XML tags. This is as opposed to a conceptual data model, which describes the semantics of an organization without reference to technology. Logical data models represent the abstract structure of a domain of information.
