posted by user: doublet || 88404 views || tracked by 373 users: [display]

KDD 2015 : 21th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

FacebookTwitterLinkedInGoogle


Conference Series : Knowledge Discovery and Data Mining
 
Link: http://www.kdd.org/kdd2015/
 
When Aug 10, 2015 - Aug 13, 2015
Where Sydney, Australia
Submission Deadline Feb 20, 2015
Notification Due May 12, 2015
Categories    data mining   knowledge discovery
 

Call For Papers

We invite submission of papers describing innovative research on all aspects of knowledge discovery and data mining, ranging from theoretical foundations to novel models and algorithms for data mining problems in science, business, medicine, and engineering. Visionary papers on new and emerging topics are also welcome, as are application-oriented papers that make innovative technical contributions to research. Authors are explicitly discouraged from submitting incremental results that do not provide significant advances over existing approaches.

Papers submitted to the Research Track are solicited in all areas of data mining, knowledge discovery, and large-scale data analytics, including, but not limited to:

Big Data: Efficient and distributed data mining platforms and algorithms, systems for large-scale data analytics of textual and graph data, large-scale machine learning systems, distributed computing (cloud, map-reduce, MPI), large-scale optimization, and novel statistical techniques for big data.

Data Science: Methods for analyzing scientific data, business data, social network analysis, recommender systems, mining sequences, time series analysis, online advertising, bioinformatics, systems biology, text/web analysis, mining temporal and spatial data, and multimedia processing.

Foundations of Data Mining: Data mining methodology, data mining model selection, visualization, asymptotic analysis, information theory, security and privacy, graph and link mining, rule and pattern mining, web mining, dimensionality reduction and manifold learning, combinatorial optimization, relational and structured learning, matrix and tensor methods, classification and regression methods, semi-supervised learning, and unsupervised learning and clustering.

Related Resources

KDD 2020   KDD 2020
WSDM 2021   14th ACM Conference on Web Search and Data Mining
CISDM 2020   2020 2nd Euro-Asia Conference on Information System and Data Mining (CISDM 2020)
AVC 2020   Advances in Vision Computing: An International Journal
ECML PKDD 2020   European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
IEEE-CVIV 2020-Ei/Scopus 2020   2020 2nd International Conference on Advances in Computer Vision, Image and Virtualization (CVIV 2020)
KDD-MLF 2020   ACM SIGKDD Workshop on Machine Learning in Finance
ICDE 2021   International Conference on Data Engineering
IEEE-CTISC 2020-Ei/Scopus 2020   2020 2nd International Conference on Advances in Computer Technology, Information Science and Communications (CTISC 2020)
COMIT 2020   4th International Conference on Computer Science and Information Technology