Titlebook: Database and Expert Systems Applications; 13th International C Abdelkader Hameurlain,Rosine Cicchetti,Roland Trau Conference proceedings 20

緯度

Domain Knowledge-Based Automatic Workflow Generationnot suitable for many cases: (a) . that cross autonomous organizationalb oundaries require experts who possess knowledge required for defining workflows composed of services from the constituent organizations; (b) . that require many variations make it infeasible and error-prone to predefine the com

意外

Facilities

Capturing Semantics in HTML Documentsstructed following some common conventions. Based on such common conventions, the Conceptual Model for HTML was proposed recently to automatically capture the hierarchical structure within web documents. However, certain key semantic information about the contents in the documents, which are obvious

健忘癥

間諜活動(dòng)

hazard

Efficient Automated Mining of Fuzzy Association Rules databases with either binary or quantitative attributes. One of these approaches is fuzzy association rules mining. However, most of the earlier algorithms proposed for mining fuzzy association rules assume that fuzzy sets are given. In this paper, we propose an automated method for autonomous mini

PACT

A Two-Phase Stock Trading System Using Distributional Differencesis paper presents a two-phase (extraction and filtering) stock trading system that aims at maximizing the rates of returns. Extraction of stocks is performed by searching specific time-series patterns described by a combination of values of technical indicators. In the filtering phase, several rules

LINE

A Multi-agent Q-learning Framework for Optimizing Stock Trading Systemseural networks are adopted for value approximation. In this framework, cooperative multiple agents are used to efficiently integrate global trend prediction and local trading strategy for obtaining better trading performance. Agents communicate with others sharing training episodes and learned polic

擋泥板

調(diào)整校對(duì)

Web Information Retrieval Based on the Localness Degreew regional area. Usually, users search for information with search engines, even though finding or excluding local information may still be difficult. In this paper,we propose a newinformation retrieval method that is based on the localness degree for discovering or excluding local information from