Pregled bibliografske jedinice broj: 141493
Coordinated Multi-Procedural Architecture for Probabilistic Knowledge Discovery
Coordinated Multi-Procedural Architecture for Probabilistic Knowledge Discovery // Proceedings of 1st International Conference on Integration of Knowledge Intensive Multi-Agent Systems (KIMAS-03), / Hexmoor, Henry (ur.).
Boston (MA): Institute of Electrical and Electronics Engineers (IEEE), 2003. str. 457-462 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 141493 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Coordinated Multi-Procedural Architecture for Probabilistic Knowledge Discovery
Autori
Bogunović, Nikola ; Ujević, Filip
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of 1st International Conference on Integration of Knowledge Intensive Multi-Agent Systems (KIMAS-03),
/ Hexmoor, Henry - Boston (MA) : Institute of Electrical and Electronics Engineers (IEEE), 2003, 457-462
Skup
International Conference on Integration of Knowledge Intensive Multi-Agent Systems (KIMAS-03)
Mjesto i datum
Boston (MA), Sjedinjene Američke Države, 30.09.2003. - 04.10.2003
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
data mining ; knowledge discovery ; knowledge representation ; multiresolutional reasoning
Sažetak
Current data mining procedures utilize operating cycles that encompass selection of the input data learning subset, filtering, application of the chosen mining algorithm, presentation of the output knowledge, and evaluation of the system performance on the unseen test data subset. However, a single pass through the above phases cannot achieve an appreciable result. The paper introduces an architecture that envelops a collection of semi-autonomous multiple procedures (agents) coupled and coordinated through the common blackboard data repository. The architecture includes an efficient performance evaluation tool that assists in tuning systems parameters during multi-resolutional construction of diverse elicited models. The presented compositional architecture is application specific and oriented towards probabilistic knowledge discovery.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Projekti:
0098023
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb,
Institut "Ruđer Bošković", Zagreb