Search results for "rule-based"

showing 10 items of 53 documents

DYNAMIC SEMANTIC USER PROFILING FROM IMPLICIT WEB NAVIGATION DATA

2014

International audience; On the Web, pages are often dynamically generated and allow publishers to individually adapt contents to each viewer. Underlying systems must correctly understand the user's context - crucial especially in the case of online advertisement placement. The article at hand describes our proposition of a novel profiling system, adapted to the special needs of digital advertising. Based on Semantic Web Technologies, the MindMinings system relies on an ontology to enable thorough understanding of each user's context and needs. The underlying ontology structure also provides enhanced interoperability with semantically annotated knowledge resources, notably vocabularies from …

JEL classification: M37 Advertising; L86 Information and Internet Services Computer Software; D80 General (Information Knowledge Uncertainty)Web Analysis[INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL]Rule-based reasoningOntologiesUser Profiling[ INFO.INFO-CL ] Computer Science [cs]/Computation and Language [cs.CL][INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]Semantic Web
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Analysis and validation in design time of distributed control systems implemented by means of rule based expert systems

2005

In this paper a new analytical method for control systems validation is presented. The control system will be implemented by means of expert systems based on rule nets, which are a formalism that seeks to express an automatism in a similar way to as would make it a human being: "IF antecedents THEN consequent". But at the same time rule nets are a tool for the design, analysis and implementation of rule based systems (RBS), and consist on a mathematic-logical structure which analytically reflects the set of rules that the human expert has designed. The validation consist on the analysis of the decisive rule nets properties in design time. This properties have been studied and formalized com…

Knowledge-based systemsCorrectnessValidation ruleAutomatic controlComputer scienceControl systemRule-based systemControl engineeringDistributed control systemcomputer.software_genrecomputerExpert systemThe Fourth International Conference on Control and Automation, 2003. ICCA. Final Program and Book of Abstracts.
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La linguistique des grammaires françaises publiées en Espagne dans la première moitié du XIXe siècle

2005

RésuméDans cet article, nous examinons un corpus de 13 grammaires pour l’enseignement du français aux Espagnols, éditées dans la première moitié du XIXe siècle. Nous prenons en compte, dans une analyse de type transversal, (1) les sources citées par les auteurs ; (2) la nature de la définition de la grammaire et le nombre des parties du discours ; (3) la définition du nom (avec la présence ou non du schéma canonique de la déclinaison ou des classes spécifiques de cet élément) ; (4) la définition du verbe avec la présence ou non des catégories canoniques) ; et (5) la syntaxe. Notre objectif est de déterminer la linguistique explicite et implicite de ces grammaires scolaires, à une époque où …

Linguistics and LanguageHistoryHistoryGrammarmedia_common.quotation_subjectVerbPart of speechLanguage and LinguisticsLinguisticsRule-based machine translationSchema (psychology)NounHistory of linguisticsDeclensionmedia_commonHistoriographia Linguistica
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Why Translation Is Difficult

2017

The paper develops a definition of translation literality that is based on the syntactic and semantic similarity of the source and the target texts. We provide theoretical and empirical evidence that absolute literal translations are easy to produce. Based on a multilingual corpus of alternative translations we investigate the effects of cross-lingual syntactic and semantic distance on translation production times and find that non-literality makes from-scratch translation and post-editing difficult. We show that statistical machine translation systems encounter even more difficulties with non-literality.

Linguistics and LanguageTranslationStatistical machine translationMachine translationComputer science02 engineering and technologycomputer.software_genreMachine translation software usability050105 experimental psychologyLanguage and LinguisticsExample-based machine translationRule-based machine translation0202 electrical engineering electronic engineering information engineeringPost-editing0501 psychology and cognitive sciencesDynamic and formal equivalencebusiness.industryCommunication05 social sciencesTransfer-based machine translationLinguisticsNon-literalityComputer-assisted translation020201 artificial intelligence & image processingSynchronous context-free grammarArtificial intelligencebusinesscomputerNatural language processingHermes
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Source-Target Mapping Model of Streaming Data Flow for Machine Translation

2017

Streaming information flow allows identification of linguistic similarities between language pairs in real time as it relies on pattern recognition of grammar rules, semantics and pronunciation especially when analyzing so called international terms, syntax of the language family as well as tenses transitivity between the languages. Overall, it provides a backbone translation knowledge for building automatic translation system that facilitates processing any of various abstract entities which combine to specify underlying phonological, morphological, semantic and syntactic properties of linguistic forms and that act as the targets of linguistic rules and operations in a source language foll…

Machine translationDeep linguistic processingbusiness.industryComputer sciencepattern recognitiondata miningTransfer-based machine translationcomputer.software_genreSemanticsmachine translationUniversal Networking LanguageRule-based machine translationComputer-assisted translationstreaming data flowArtificial intelligenceLanguage familynatural language processingbusinesscomputerNatural language processing
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Learning for allocations in the long-run average core of dynamical cooperative TU games

2011

We consider repeated coalitional TU games characterized by unknown but bounded and time-varying coalitions' values. We build upon the assumption that the Game Designer uses a vague measure of the extra reward that each coalition has received up to the current time to learn on how to re-adjust the allocations among the players. As main result, we present an allocation rule based on the extra reward variable that converges with probability one to the core of the long-run average game. Analogies with stochastic stability theory are put in evidence.

Mathematical optimizationComputer scienceRobustness (computer science)Stochastic processBounded functionRule-based systemRobust controlVideo game designGame theoryMathematical economicsUpper and lower boundsgame theory control
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Bridging data mining and semantic web

2016

Nowadays Semantic Web is widely adopted standard of knowledge representation. Hence, knowledge engineers are applying sophisticated methods to capture, discover and represent knowledge in Semantic Web form. Studies show that, to represent knowledge in Semantic Web standard, data mining techniques such as Decision Trees, Association Rules, etc., play an important role. These techniques are implemented in publicly available Data Mining tools. These tools represent knowledge discovered in human readable format and some tools use Predictive Model Markup language (PMML). PMML is an XML based model for data mining model representation that fails to address the representation of the semantics of t…

PMMLOntologyDecision Treeontologiasemanttinen webSematic webRule-based knowledgeSWRL
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Process specification and verification

1996

Graph grammars provide a very convenient specification tool for distributed systems of processes. This paper addresses the problem how properties of such specifications can be proven. It shows a connection between algebraic graph rewrite rules and temporal (trace) logic via the graph expressions of [2]. Statements concerning the global behavior can be checked by local reasoning.

Predicate logicGraph rewritingWait-for graphTheoretical computer scienceComputer scienceProgramming languagecomputer.software_genreLanguage Of Temporal Ordering SpecificationRule-based machine translationGraph (abstract data type)Temporal logicAlgebraic numbercomputerComputer Science::Databases
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Does the mastery of center-embedded linguistic structures distinguish humans from nonhuman primates?

2005

In a recentScience article, Fitch and Hauser (2004; hereafter, F&H) claimed to have demonstrated that cotton-top tamarins fail to learn an artificial language produced by a phrase structure grammar (Chomsky, 1957) generating center-embedded sentences, whereas adult humans easily learn such a language. We report an experiment replicating the results of F&H in humans but also showing that subjects learned the language without exploiting in any way the center-embedded structure. When the procedure was modified to make the processing of this structure mandatory, the subjects no longer showed evidence of learning. We propose a simple interpretation for the difference in performance observed in F…

PrimatesStructure (mathematical logic)HierarchyInterpretation (logic)Grammarmedia_common.quotation_subjectAptitudeLinguisticsRecognition PsychologyExperimental and Cognitive PsychologyLinguisticsTask (project management)Constructed languageCognitionArts and Humanities (miscellaneous)Rule-based machine translationSpeech PerceptionDevelopmental and Educational PsychologyAnimalsHumansLearningPhrase structure grammarPsychologymedia_commonPsychonomic Bulletin & Review
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Structural Knowledge Extraction from Mobility Data

2016

Knowledge extraction has traditionally represented one of the most interesting challenges in AI; in recent years, however, the availability of large collections of data has increased the awareness that “measuring” does not seamlessly translate into “understanding”, and that more data does not entail more knowledge. We propose here a formulation of knowledge extraction in terms of Grammatical Inference (GI), an inductive process able to select the best grammar consistent with the samples. The aim is to let models emerge from data themselves, while inference is turned into a search problem in the space of consistent grammars, induced by samples, given proper generalization operators. We will …

Process (engineering)Computer scienceGeneralizationmedia_common.quotation_subjectInference02 engineering and technologyMachine learningcomputer.software_genreTheoretical Computer ScienceGrammatical inferenceKnowledge extractionRule-based machine translation020204 information systems0202 electrical engineering electronic engineering information engineeringSearch problemmedia_commonStructural knowledgeGrammarbusiness.industryMobility dataComputer Science (all)020207 software engineeringGrammar inductionArtificial intelligencebusinesscomputerNatural language processing
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