posted by user: doublet || 114650 views || tracked by 368 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 2023   29TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING
SDM 2023   SDM 2023 : SIAM International Conference on Data Mining
ACM-Ei/Scopus-CWCBD 2023   2023 4th International Conference on Wireless Communications and Big Data (CWCBD 2023) -EI Compendex
ICDM 2023   International Conference on Data Mining
DS 2023   Discovery Science 2023
MLDM 2023   19th International Conference on Machine Learning and Data Mining
DAWAK 2023   The 25th International Conference on Big Data Analytics and Knowledge Discovery
ESANN 2023   European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
ACM ICCBDC 2023   ACM--2023 7th International Conference on Cloud and Big Data Computing (ICCBDC 2023)
DKMP 2023   11th International Conference on Data Mining & Knowledge Management Process