Titlebook: Autonomous Intelligent Systems: Agents and Data Mining; International Worksh Vladimir Gorodetsky,Jiming Liu,Victor A. Skormin Conference pr

curriculum

Meta-reasoning Methods for Agent’s Intention Modelling and meta-reasoning in intention modelling. The formal model of deductive and inductive meta-reasoning is presented and supported by experimental implementations. This research has been motivated by the problem of intention detection in semi-collaborative multi-agent system for OOTW (Operation Other

Bureaucracy

褪色

A Methodology for Predicting Agent Behavior by the Use of Data Mining Techniquesmpting to optimally reflect both the inner states, as well as the perceived environment of an agent, in order to provide it either with reactivity or proactivity. Within the context of this paper, an alternative methodology for enhancing agent behavior is presented. The core feature of this methodol

遺忘

Oligarchy

Parallel Algorithm for Mining Frequent Closed Sequencessed ones because the latter leads to not only more compact yet complete result set but also better efficiency. However, frequent closed sequence mining is still challenging on stand-alone for its large size and high dimension. In this paper, an algorithm, PFCSeq, is presented for mining frequent clo

GNAW

SSRIS

Querying Dynamic and Context-Sensitive Metadata in Semantic Web such as web pages, files, databases, services, etc., which structure and content are more or less stable. However, on the other hand, emerging industrial applications consider e.g. machines, processes, personnel, services for condition monitoring, remote diagnostics and maintenance, etc. to be spec

束縛

Ontology Issue in Multi-agent Distributed Learningtributes to the further progress in both above areas and provides practitioners with a new kind of technology of distributed intelligent systems. However, this integration generates a number of new non-typical problems both in areas, data mining and multi-agent systems. This fact is explicitly confi

束縛

Ontology-Based Users and Requests Clustering in Customer Service Management Systemrocedures. Today this kind of activities is implemented through e-services to directly involve customers into business processes. Traditionally Customer Service Management involves application of data mining techniques to discover usage patterns from the company knowledge memory. Hence grouping of c

infatuation