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2010 | nr 133 Pozyskiwanie wiedzy i zarządzanie wiedzą | 42-57
Tytuł artykułu

Kontekst w uczeniu się pojęć

Warianty tytułu
Context in Concept Learning
Języki publikacji
Rosnące woluminy, wzrastająca złożoność, wielość źródeł, a także cele gromadzenia danych różne od realizowanych zadań analizy danych są jedną z przyczyn niepowodzeń algorytmów uczenia się pojęć. Szczególnego znaczenia nabierają upraszczające i nieadekwatne do rzeczywistości założenia. Dotyczą one precyzyjności pojęć, kontekstowej niezależności oraz możliwości reprezentacji pojęcia przez pojedynczy opis symboliczny. Przegląd sposobów uwolnienia tych założeń i poszerzenie opisu pojęć o zależności kontekstowe są przedmiotem artykułu. (abstrakt oryginalny)
Growing volumes and complexity, big number of sources and goals of gathering data that are different than data analysis tasks are the main reason of failure of concept learning algorithms. Simplistic and inadequate to the reality assumptions become significant. They concern accuracy of concepts, contextual independency and possibility to represent concept by a single nominal description. This paper presents an overview of ways to unchain those assumptions and broadening description of concepts by contextual dependency. (original abstract)
  • Uniwersytet Ekonomiczny we Wrocławiu
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