黃金海岸，澳大利亞（Gold Coast，Australia）

2013年4月14日～2013年4月17日

http：//pakdd2013.pakdd.org/

Important Dates

Paper submission due：Oct.1 （Mon）.2012 Notification to author：Dec.19 （Wed）.2012

Camera ready due：Jan.6 （Sun）.2013

＊［23：59：59 Pacific Standard Time］

Conference Scope

The Pacific－Asia Conference on Knowledge Discovery and Data Mining（PAKDD）is a leading international conference in the areas of data mining and？knowledge discovery（KDD）.It provides an international forum for researchers and industry practitioners to share their new ideas，original research？results and practical development experiences from all KDD related areas，including data mining，data warehousing，machine learning，artificial？intelligence，databases，statistics，knowledge engineering，visualization，and decision－making systems.The conference calls for research papers？reporting original investigation results and industrial papers reporting real data mining applications and system development experience.

Topics

The topics of relevance for the conference papers include but not limited to the following：

·Novel models and algorithms·Visual data mining

·Clustering·Interactive and online mining

·Classification·Mining behavioral data

·Ranking·Mining multimedia data

·Association analysis·Mining scientific databases

·Anomaly detection·Ubiquitous knowledge discovery

·Data pre－processing·Agent－based data mining

·Feature extraction and selection·Mining social networks

·Mining heterogeneous data·Financial data mining

·Mining multi－source data·Fraud and risk analysis

·Mining sequential data·Security and intrusion detection

·Mining spatial and temporal data·O inion minin and sentiment anal sis

·Mining unstructured and semi structured data p g y

－·Post processing including quality assessment and

·Mining graph and network data－

·Parallel，distributed，and high performance data validation

mining on the cloud platform·Integration of data warehousing，OLAP and data

·Privacy preserving data mining mining

·Mining high dimensional data·Human，domain，organizational and social factors in

·Mining uncertain data data mining

·Mining imbalanced data·Applications to healthcare，bioinformatics，compu－

·Mining dynamic/streaming data tational chemistry，

·Statistical methods for data mining·Eco－informatics，marketing，online gaming，etc