<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">T.P. Dobrowiecki</style></author><author><style face="normal" font="default" size="100%">G. Strausz</style></author><author><style face="normal" font="default" size="100%">T. Mészáros</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Knowledge Fusion for Financial Advisory Applications</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 7th Biennial Conference on Electronics and Microsys tem Technology, Baltic Electronics Conference</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2000</style></year></dates><pub-location><style face="normal" font="default" size="100%">Tallinn, Estonia</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In the paper we present a design of a decision support system for the fully automated controlled retrieval of fiscal information, which is being continuously collected from a variety of sources, mainly from the global computer network. This system extends the idea of data mining to the notion of knowledge retrieval. The collected information is processed in a knowledge-intensive way using knowledge models of the application domain and can subsequently be used to support various decision-making processes.</style></abstract></record></records></xml>