Pregled bibliografske jedinice broj: 720153
Multilayer clustering: A discovery experiment on country level trading data
Multilayer clustering: A discovery experiment on country level trading data // 17th International Conference Dicovery Science 2014 / Džeroski, Sašo ; Panov, Panče ; Kocev, Dragi ; Todorovski, Ljupčo (ur.).
Heidelberg: Springer, 2014. str. 87-98 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 720153 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Multilayer clustering: A discovery experiment on country level trading data
Autori
Gamberger, Dragan ; Mihelčić, Matej ; Lavrač, Nada
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
17th International Conference Dicovery Science 2014
/ Džeroski, Sašo ; Panov, Panče ; Kocev, Dragi ; Todorovski, Ljupčo - Heidelberg : Springer, 2014, 87-98
ISBN
978-3-319-11811-6
Skup
International Conference Discovery Science
Mjesto i datum
Bled, Slovenija, 08.10.2014. - 10.10.2014
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Data clustering; Multilayer clustering; Data analysis application
Sažetak
The topic of this work is the presentation of a novel clustering methodology based on instance similarity in two or more attribute layers. The work is motivated by multi-view clustering and redescription mining algorithms. In our approach we do not construct descriptions of subsets of instances and we do not use conditional independence assumption of different views. We do bottom up merging of clusters only if it enables reduction of an example variability score for all layers. The score is defined as a two component sum of squared deviates of example similarity values. For a given set of instances, the similarity values are computed by execution of an artificially constructed supervised classification problem. As a final result we identify a small but coherent clusters. The methodology is illustrated on a real life discovery task aimed at identification of relevant subgroups of countries with similar trading characteristics in respect of the type of commodities they export.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Projekti:
HRZZ-IP-2013-11-9623 - Postupci strojnog učenja za dubinsku analizu složenih struktura podataka (DescriptiveInduction) (Gamberger, Dragan, HRZZ - 2013-11) ( CroRIS)
Ustanove:
Institut "Ruđer Bošković", Zagreb
Citiraj ovu publikaciju:
Časopis indeksira:
- Scopus