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Enregistrement W2577231901 · doi:10.20965/jaciii.2005.p0003

Intelligent Systems: Methodology, Models, and Applications in Emerging Technologies

2005· article· en· W2577231901 sur OpenAlexaboutno aff
Vassil Sgurev, Vladimir Jotsov, Mincho Hadjiski

Notice bibliographique

RevueJournal of Advanced Computational Intelligence and Intelligent Informatics · 2005
Typearticle
Langueen
DomaineComputer Science
ThématiqueFuzzy Logic and Control Systems
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésIntelligent decision support systemComputer scienceOntologyIntelligent agentFuzzy logicIntelligent controlArtificial intelligenceAgent architectureSemantics (computer science)Data science

Résumé

récupéré en direct d'OpenAlex

From year to year the number of investigations on intelligent systems grows rapidly. For example this year 245 papers from 45 countries were sent for the Second International IEEE Conference on Intelligent Systems (www.ieee-is.org; www.fnts-bg.org/is) and this is an increase of more than 50% by all indicators. The presented papers on intelligent systems were marked by big audiences and they provoked a significant interest that ultimately led to the formation of vivid discussions, exchange of ideas and locally provoked the creation of working groups for different applied projects. All this reflects the worldwide tendencies for the leading role of the research on intelligent systems theoretically and practically. The greater part of the presented research dealt with traditional for the intelligent systems problems like artificial intelligence, knowledge engineering, intelligent agents, neural and fuzzy networks, intelligent data processing, intelligent control and decision making systems, and also new interdisciplinary problems like ontology and semantics in Internet, fuzzy intuitionistic logic. The majority of papers from the European and American researchers are dedicated to the theory and the applications of the intelligent systems with machine learning, fuzzy inference or uncertainty. Another big group of papers focuses on the domain of building and integrating ontologies of applications with heterogeneous multiagent systems. A great number of papers on intelligent systems deals with fuzzy sets. The papers of many other researchers underscore the significance of the contemporary perception-oriented methods and also of different applications in the intelligent systems. On the first place this is valid for the paradigm of L. A. Zadeh 'computing with words'. The Guest Editors in the present specialized journal volume would like to introduce a wealth of research with an applied and theoretical character that possesses a common characteristic and it is the conference best papers complemented and updated by the new elaborations of the authors during the last half a year. A short description of the presented in the volume papers follows. In 'Combining Local and Global Access to Ontologies in a Multiagent System' R. Brena and H. Ceballos (Mexico) proposed an original way for operation with ontologies where a part of the ontology is processed by a client's component and the rest is transmitted to the other agents by an ontology agent. The inter-agent communication is improved in this way. In 'Fuzzy Querying of Evolutive Situations: Application to Driving Situations' S. Ould Yahia and S. Loriette-Rougegrez (France) present an approach to analysis of driving situations using multimedia images and fuzzy estimates that will improve the driver's security. In 'Rememberng What You Forget in an Online Shopping Context' M. Halvey and M. Keane (Ireland) presented their approach to constructing online system that predicts the items for future shopping sessions using a novel idea called Memory Zones. In 'Reinforcement Learning for Online Industrial Process Control' the authors J. Govindhasamy et al. (Ireland) use a synthesis of dynamic programming, reinforcement learning and backpropagation for a goal of modeling and controlling an industrial grinding process. The felicitous combination of methods contributes for a greater effectiveness of the applications compared to the existing controllers. In 'Dynamic Visualization of Information: From Database to Dataspace' the authors C. St-Jacques and L. Paquin (Canada) suggested a friendly online access to large multimedia databases. W. Huang (UK) redefines in 'Towards Context-Aware Knowledge Management in e-Enterprises' the concept of context in intelligent systems and proposes a set of meta-information elements for context description in a business environment. His approach is applicable in the E-business, in the Semantic Web and in the Semantic Grid. In 'Block-Based Change Detection in the Presence of Ambient Illuminaion Variations' T. Alexandropoulos et al. (Greece) use a statistic analysis, clustering and pattern recognition algorithms, etc. for the goal of noise extraction and the global illumination correction. In 'Combining Argumentation and Web Search Technology: Towards a Qualitative Approach for Ranking Results' C. Chesñevar (Spain) and A. Maguitman (USA) proposed a recommender system for improving the WEB search. Defeasible argumentation and decision support methods have been used in the system. In 'Modified Axiomatic Basis of Subjective Probability' K. Tenekedjiev et al. (Bulgaria) make a contribution to the axiomatic approach to subjective uncertainty by introducing a modified set of six axioms to subjective probabilities. In 'Fuzzy Rationality in Quantitative Decision Analysis' N. Nikolova et al. (Bulgaria) present a discussion on fuzzy rationality in the elicitation of subjective probabilities and utilities. The possibility to make this special issue was politely offered to the Guest Editors by Prof. Kaoru Hirota, Prof. Toshio Fukuda and we thank them for that. Due to the help of Kenta Uchino and also due to the new elaborations presented by explorers from Europe and America the appearance of this special issue became possible.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,005
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: Théorique ou conceptuel
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,009
Score d'incertitude au seuil0,025

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,005
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0030,004
Études des sciences et des technologies0,0010,007
Communication savante0,0090,007
Science ouverte0,0030,003
Intégrité de la recherche0,0040,004
Charge utile insuffisante (le modèle a refusé de juger)0,0060,003

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,061
Tête enseignante GPT0,317
Écart entre enseignants0,256 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeThéorique ou conceptuel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2005
Routes d'admission1
Résumé présentoui

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