Advances in Data Analysis, Data Handling and Business Intelligence Advances in Data Analysis, Data Handling and Business Intelligence
Studies in Classification, Data Analysis, and Knowledge Organization

Advances in Data Analysis, Data Handling and Business Intelligence

Proceedings of the 32nd Annual Conference of the Gesellschaft für Klassifikation e.V., Joint Conference with the British Classification Society (BCS) and the Dutch/Flemish Classification Society (VOC), Helmut-Schmidt-University, Hamburg, July 16-18, 2008

Andreas Fink 및 다른 저자
    • US$189.99
    • US$189.99

출판사 설명

Data Analysis, Data Handling and Business Intelligence are research areas at the intersection of computer science, artificial intelligence, mathematics, and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as in marketing, finance, economics, engineering, linguistics, archaeology, musicology, medical science, and biology. This volume contains the revised versions of selected papers presented during the 32nd Annual Conference of the German Classification Society (Gesellschaft für Klassifikation, GfKl). The conference, which was organized in cooperation with the British Classification Society (BCS) and the Dutch/Flemish Classification Society (VOC), was hosted by Helmut-Schmidt-University, Hamburg, Germany, in July 2008.

장르
컴퓨터 및 인터넷
출시일
2009년
10월 14일
언어
EN
영어
길이
721
페이지
출판사
Springer Berlin Heidelberg
판매자
Springer Nature B.V.
크기
17.9
MB

비슷한 책 더 보기

Classification - the Ubiquitous Challenge Classification - the Ubiquitous Challenge
Classification - the Ubiquitous Challenge
2006년
Machine Learning and Data Mining in Pattern Recognition Machine Learning and Data Mining in Pattern Recognition
Machine Learning and Data Mining in Pattern Recognition
2009년
Advances in Intelligent Data Analysis VII Advances in Intelligent Data Analysis VII
Advances in Intelligent Data Analysis VII
2007년
COMPSTAT 2008 COMPSTAT 2008
COMPSTAT 2008
2008년
Knowledge Discovery in Databases: PKDD 2007 Knowledge Discovery in Databases: PKDD 2007
Knowledge Discovery in Databases: PKDD 2007
2007년
Intelligent Data Engineering and Automated Learning -- IDEAL 2011 Intelligent Data Engineering and Automated Learning -- IDEAL 2011
Intelligent Data Engineering and Automated Learning -- IDEAL 2011
2011년

Andreas Fink, Berthold Lausen, Wilfried Seidel & Alfred Ultsch의 도서 더 보기

GEGEN UNENDLICH. Phantastische Geschichten – Nr. 15 GEGEN UNENDLICH. Phantastische Geschichten – Nr. 15
GEGEN UNENDLICH. Phantastische Geschichten – Nr. 15
2019년
Operations Research Proceedings 2016 Operations Research Proceedings 2016
Operations Research Proceedings 2016
2017년
Grundlagen der Wirtschaftsinformatik Grundlagen der Wirtschaftsinformatik
Grundlagen der Wirtschaftsinformatik
2006년
Applications of Evolutionary Computing Applications of Evolutionary Computing
Applications of Evolutionary Computing
2008년
Applications of Evolutionary Computing Applications of Evolutionary Computing
Applications of Evolutionary Computing
2009년
Advances and Applications in Sliding Mode Control systems Advances and Applications in Sliding Mode Control systems
Advances and Applications in Sliding Mode Control systems
2008년

이 시리즈의 다른 책

Data Science Data Science
Data Science
2017년
Challenges at the Interface of Data Analysis, Computer Science, and Optimization Challenges at the Interface of Data Analysis, Computer Science, and Optimization
Challenges at the Interface of Data Analysis, Computer Science, and Optimization
2012년
Statistical Models and Learning Methods for Complex Data Statistical Models and Learning Methods for Complex Data
Statistical Models and Learning Methods for Complex Data
2025년
Supervised and Unsupervised Statistical Data Analysis Supervised and Unsupervised Statistical Data Analysis
Supervised and Unsupervised Statistical Data Analysis
2025년
Recent Trends and Future Challenges in Learning from Data Recent Trends and Future Challenges in Learning from Data
Recent Trends and Future Challenges in Learning from Data
2024년
Statistical Models and Methods for Data Science Statistical Models and Methods for Data Science
Statistical Models and Methods for Data Science
2023년