posted by user: doublet || 110132 views || tracked by 370 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 2022   28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
ICDM 2022   22nd IEEE International Conference on Data Mining
MLDM 2023   18th International Conference on Machine Learning and Data Mining
ADMA 2022   18th International Conference on Advanced Data Mining and Applications
ICMLA 2022   IEEE International conference on Machine Learning and Applications
ADMA 2022   18th International Conference on Advanced Data Mining and Applications
ACM-Ei/Scopus-ITNLP 2022   2022 2nd International Conference on Information Technology and Natural Language Processing (ITNLP 2022) -EI Compendex
MSR4P&S 2022   International Workshop on Mining Software Repositories Applications for Privacy and Security (co-located with ESEC/FSE)
WSDM 2023   Web Search and Data Mining
CD 2022   The 2022 ACM SIGKDD Workshop on Causal Discovery