Abstrakt
This article presents a survey on the use of KREM, a generic knowledge-based framework for building collective intelligence through experience. After a discussion on the disadvantages of the traditional architecture used to deploy intelligent systems, the KREM architecture (Knowledge, Rules, Experience, Meta-Knowledge) is presented. The novelty of the proposal comes from the inclusion of the capitalisation of experience and the use of meta-knowledge in the traditional architecture previously discussed. KREM improves the efficiency of traditional intelligent systems by allowing incomplete expert knowledge models to be used, gradually completing them, learning with experience. In addition, the use of meta-knowledge can guide their execution more effectively. This framework has been successfully used in various projects in different application areas, which are presented and discussed.
Cytowania
-
0
CrossRef
-
0
Web of Science
-
1
Scopus
Autorzy (2)
Cytuj jako
Pełna treść
pełna treść publikacji nie jest dostępna w portalu
Słowa kluczowe
Informacje szczegółowe
- Kategoria:
- Publikacja w czasopiśmie
- Typ:
- artykuły w czasopismach
- Opublikowano w:
-
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
nr 37,
strony 7141 - 7153,
ISSN: 1064-1246 - Język:
- angielski
- Rok wydania:
- 2019
- Opis bibliograficzny:
- Zanni-Merk C., Szczerbicki E.: Building collective intelligence through experience: a survey on the use of the KREM model// JOURNAL OF INTELLIGENT & FUZZY SYSTEMS -Vol. 37,iss. 6 (2019), s.7141-7153
- DOI:
- Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.3233/jifs-179327
- Weryfikacja:
- Politechnika Gdańska
wyświetlono 125 razy
Publikacje, które mogą cię zainteresować
Smart Knowledge Engineering for Cognitive Systems: A Brief Overview
- C. Silva de Oliveira,
- C. Sanin,
- E. Szczerbicki
Experience based knowledge representation for Internet of Things and Cyber Physical Systems with case studies
- C. Sanin,
- Z. Haoxi,
- I. Shafiq
- + 3 autorów
Developing an Ontology from Set of Experience KnowledgeStructure
- C. Sanin,
- E. Szczerbicki,
- C. Toro