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[null,"1.","Record Nr.",null,"UNISA996198512903316"]
[null,null,"Titolo",null,"Machine Learning and Data Mining in Pattern Recognition [[electronic resource] ] : 11th International Conference, MLDM 2015, Hamburg, Germany, July 20-21, 2015, Proceedings / / edited by Petra Perner"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015"]
[null,null,"ISBN",null,"3-319-21024-6"]
[null,null,"Edizione",null,"[1st ed. 2015.]"]
[null,null,"Descrizione fisica",null,"1 online resource (IX, 454 p. 132 illus.)"]
[null,null,"Collana",null,"Lecture Notes in Artificial Intelligence ; ; 9166"]
[null,null,"Disciplina",null,"006.4"]
[null,null,"Soggetti",null,"Data mining"]
[{"$nulls":4},"Pattern recognition"]
[{"$nulls":4},"Algorithms"]
[{"$nulls":4},"Application software"]
[{"$nulls":4},"Database management"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Data Mining and Knowledge Discovery"]
[{"$nulls":4},"Pattern Recognition"]
[{"$nulls":4},"Algorithm Analysis and Problem Complexity"]
[{"$nulls":4},"Information Systems Applications (incl. Internet)"]
[{"$nulls":4},"Database Management"]
[{"$nulls":4},"Artificial Intelligence"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Bibliographic Level Mode of Issuance: Monograph"]
[null,null,"Nota di contenuto",null,"Graph Mining -- Classification and regression -- Sentiment analysis -- Data preparation and missing values -- Association and sequential rule mining -- Support vector machines -- Frequent item set mining and time series analysis -- Clustering -- Text mining -- Applications data mining."]
[null,null,null,"Sommario/riassunto","This book constitutes the refereed proceedings of the 11th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2015, held in Hamburg, Germany, in July 2015. The 41 full papers presented were carefully reviewed and selected from 123 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types "]
[{"$nulls":4},"such as image mining, text mining, video mining and Web mining."]