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Record Nr. |
UNISA996465791103316 |
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Titolo |
Data Mining and Big Data [[electronic resource] ] : First International Conference, DMBD 2016, Bali, Indonesia, June 25-30, 2016. Proceedings / / edited by Ying Tan, Yuhui Shi |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
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ISBN |
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Edizione |
[1st ed. 2016.] |
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Descrizione fisica |
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1 online resource (XVI, 569 p. 141 illus.) |
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Collana |
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Information Systems and Applications, incl. Internet/Web, and HCI ; ; 9714 |
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Disciplina |
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Soggetti |
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Pattern recognition |
Artificial intelligence |
Application software |
Information storage and retrieval |
Database management |
Algorithms |
Pattern Recognition |
Artificial Intelligence |
Information Systems Applications (incl. Internet) |
Information Storage and Retrieval |
Database Management |
Algorithm Analysis and Problem Complexity |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Challenges in Data Mining and Big Data -- Data Mining Algorithms -- Frequent Itemset Mining -- Spatial Data Mining -- Prediction -- Feature Selection -- Information Extraction -- Classification -- Anomaly Pattern and Diagnosis -- Data Visualization Analysis -- Privacy Policy -- Social Media -- Query Optimization and Processing Algorithm -- Big Data -- Computational Aspects of Pattern Recognition and Computer Vision. |
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Sommario/riassunto |
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The LNCS volume LNCS 9714 constitutes the refereed proceedings of |
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the International Conference on Data Mining and Big Data, DMBD 2016, held in Bali, Indonesia, in June 2016. The 57 papers presented in this volume were carefully reviewed and selected from 115 submissions. The theme of DMBD 2016 is "Serving Life with Data Science". Data mining refers to the activity of going through big data sets to look for relevant or pertinent information. The papers are organized in 10 cohesive sections covering all major topics of the research and development of data mining and big data and one Workshop on Computational Aspects of Pattern Recognition and Computer Vision. |
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