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uma modelagem dos processos cognitivo, emocional e motivacional
uma modelagem dos processos cognitivo, emocional e motivacional

querying description logic knowledge bases
querying description logic knowledge bases

... defined syntax and semantics. A Description Logic allows for the specification of concepts (also known as classes), individuals (also known as objects) that are instances of these concepts, and roles (also known as properties) that are interpreted as pairs of individuals that are related by the role ...
The DL-Lite Family - Dipartimento di Informatica e Sistemistica
The DL-Lite Family - Dipartimento di Informatica e Sistemistica

... An interpretation I is a model of an inclusion assertion B ⊑ C, if B I ⊆ C I . We extend the notion of model also to inclusion assertions of more general forms with respect to the one allowed in DL-Litecore . An interpretation I is a model of C1 ⊑ C2 , where C1 , C2 are general concepts, if C1I ⊆ C2 ...
Algorithms and Arguments Artificial Intelligence
Algorithms and Arguments Artificial Intelligence

... involve four tolerably distinct steps. even if human reasoning were based on algorithms, it could not be considered as a mechanical computation: “There is, first, the statement of our data in accurate logical language. [...] Then secondly, we have to throw these statements into a form fit for the en ...
questions and answers: reasoning and querying in description logic
questions and answers: reasoning and querying in description logic

... Description Logics (DLs) are a family of formal languages for describing complex structured classes. These languages contain boolean operators and quantification over class attributes, as well as the specification of elements of the classes and their properties. DL knowledge bases (KBs) consist of a ...
On skew Heyting algebras - ars mathematica contemporanea
On skew Heyting algebras - ars mathematica contemporanea

... provide algebraic models of intuitionistic logic. In the present paper we introduce the notion of a skew Heyting algebra. In passing to the non-commutative setting one needs to sacrifice either the top or the bottom of the algebra in order not to end up in the commutative setting. In the previous pa ...
The Exploration of Greedy Hill-climbing Search in Markov
The Exploration of Greedy Hill-climbing Search in Markov

... spanning tree (MWST) using mutual information, and then using the topological order of the oriented MWST as the initial node sequence. The greedy Hill-climbing algorithm in the DAG space (GS algorithm) takes an initial graph, defines a neighborhood, computes a score for every graph in this neighborh ...
Semantic Enrichment - UMKC School of Computing and Engineering
Semantic Enrichment - UMKC School of Computing and Engineering

... Terminological Knowledge Bases [1] are ontologies or terminologies that consist of an upper layer of semantic types (broad categories) and a lower layer of concepts. The two preeminent examples of terminologies with a two-level structure are the Unified Medical Language System (UMLS) [2-4] and the W ...
ITM-05-OO+Ontologies
ITM-05-OO+Ontologies

... An ontology should be coherent: that is, it should sanction inferences that are consistent with the definitions.[…] If a sentence that can be inferred from the axioms contradicts a definition or example given informally, then the ontology is incoherent. ...
Semantic Enrichment - UMKC School of Computing and Engineering
Semantic Enrichment - UMKC School of Computing and Engineering

... according to the UMLS. We showed that the two-level ontology reduced the likelihood of false positives, since we avoided matching concepts of different semantics, which out of principle cannot be the same, as long as all semantic type assignments are correct. Using the two level ontology leads to be ...
Schematic Invariants by Reduction to Ground Invariants
Schematic Invariants by Reduction to Ground Invariants

... typed schematic language for expressing actions and invariants.1 Definition 1 (Types) Let O be a set of objects. Let there be a finite set T of types, and to each type t ∈ T a non-empty set D(t) ⊆ O of objects is associated by the domain function D : T → O. The objects of different types do not need ...
Sample chapter - Computer Science and Software Engineering
Sample chapter - Computer Science and Software Engineering

... One is cognitive economy, calling for grouping similar things together and giving them a name. The other principle is rather a recognition that the continuous world outside of the body is actually structured and forms natural discontinuities. Categories are then, economically, formed by objects that ...
Computability of Heyting algebras and Distributive Lattices
Computability of Heyting algebras and Distributive Lattices

... computability theory (cf., e.g., [18]). Fix an enumeration of the partial computable functions ϕ0 , ϕ1 , ϕ2 , . . . , and write ϕe converges to y on input x as ϕe (x) ↓= y and ϕe diverges on input x as ϕe (x) ↑. If ϕe (x) converges, it does so after a finite number of steps. Denote ϕe (x) converges ...
WordNet::Similarity - Measuring the Relatedness of Concepts
WordNet::Similarity - Measuring the Relatedness of Concepts

... and relatedness that are all in some way based on the structure and content of WordNet. Measures of similarity use information found in an is– a hierarchy of concepts (or synsets), and quantify how much concept A is like (or is similar to) concept B. For example, such a measure might show that an au ...
Oriented Flip Graphs and Noncrossing Tree Partitions
Oriented Flip Graphs and Noncrossing Tree Partitions

... then the equivalence relation x ” y mod Θ if πÓ pxq “ πÓ pyq is a lattice congruence. Given x, y in a poset P , we say y covers x, denoted x Ì y, if x ă y and there does not exist z P P such that x ă z ă y. We let CovpP q denote the set of all covering relations of P . If P is finite, then the parti ...
FS-FOIL: An Inductive Learning Method for Extracting Interpretable
FS-FOIL: An Inductive Learning Method for Extracting Interpretable

... There is no unique commonly accepted one-sentence definition of data mining, machine learning, or the more general term information mining that has become fashionable in the last few years. In the authors’ humble opinion, “the non-trivial extraction of implicit, previously unknown, and potentially u ...
Steps toward Formalizing Context - Bilkent University Computer
Steps toward Formalizing Context - Bilkent University Computer

... AI MAGAZINE ...
An Investigation of the Cost and Accuracy Tradeoffs of Supplanting... in Query Processing in the Presence of Incompleteness in Autonomous...
An Investigation of the Cost and Accuracy Tradeoffs of Supplanting... in Query Processing in the Presence of Incompleteness in Autonomous...

... more and more information in autonomous databases. Incompleteness in these autonomous sources is extremely commonplace. Such incompleteness mainly arises due to the way in which these databases are populated- through (inaccurate) automatic extraction or by lay users. Dealing with incompleteness in t ...
Paper  - FB3
Paper - FB3

... inexpressive concrete domain based on the natural numbers and providing for equality and incrementation predicates is undecidable, see also the survey paper [23]. In view of this discouraging result, it is a natural question whether there are any useful concrete domains that can be combined with gen ...
Meinongian Semantics and Artificial Intelligence
Meinongian Semantics and Artificial Intelligence

... A semantic network is a representational system consisting of a graph (usually a labeled, directed graph), whose nodes represent objects and whose arcs represent relations among them. There have been several different kinds in the literature (see Sowa 1992, 2002 for a general introduction to them, a ...
Formalizing Context (Expanded Notes) - John McCarthy
Formalizing Context (Expanded Notes) - John McCarthy

... c, itself asserted in an outer context c0 . (We have adopted Guha’s [29] notation rather than that of [39], because he built his into Cyc, and it was easy for us to change ours.) For now, propositions may be identified with sentences in English or in various logical languages, but we may later take ...
From Agent Theory to Agent Construction: A Case Study
From Agent Theory to Agent Construction: A Case Study

... distinguish between them [16]. The critical distinction that we do make, however, is that between agents and autonomous agents, an important aspect often overlooked. In short, we propose a four-tiered hierarchy of entities comprising entities, objects, agents and autonomous agents. The basic idea un ...
From Agent Theory to Agent Construction: A Case Study
From Agent Theory to Agent Construction: A Case Study

... distinguish between them [16]. The critical distinction that we do make, however, is that between agents and autonomous agents, an important aspect often overlooked. In short, we propose a four-tiered hierarchy of entities comprising entities, objects, agents and autonomous agents. The basic idea un ...
Top-Down Induction of Decision Trees Classifiers – A Survey
Top-Down Induction of Decision Trees Classifiers – A Survey

... Originally the machine learning community has introduced the problem of Concept Learning. To learn a concept is to infer its general definition from a set of examples. This definition may be either explicitly formulated or left implicit, but either way it assigns each possible example to the concept ...
Levels of Organization in General Intelligence
Levels of Organization in General Intelligence

... postulate that Eurisko was treated as a failed hypothesis, or even as a competing hypothesis, rather than an incremental success or a reusable tool. Lenat tried self-optimizing heuristics and they failed to yield intelligence; onward, then, to Cyc, the next hypothesis! The most common paradigms of t ...
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Formal concept analysis

In information science, formal concept analysis is a principled way of deriving a concept hierarchy or formal ontology from a collection of objects and their properties. Each concept in the hierarchy represents the set of objects sharing the same values for a certain set of properties; and each sub-concept in the hierarchy contains a subset of the objects in the concepts above it. The term was introduced by Rudolf Wille in 1984, and builds on applied lattice and order theory that was developed by Garrett Birkhoff and others in the 1930s.Formal concept analysis finds practical application in fields including data mining, text mining, machine learning, knowledge management, semantic web, software development, chemistry and biology.
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