CFP: DTWSM2015

The 2nd IEEE International Workshop on Data, Text, Web and Social Networking Mining (DTWSM 2015)

   https://research.comnet.aalto.fi/BDSE2015/dtwsm2015/

Important Dates
Submission deadline: March 31, 2015
Authors notification: May 31, 2015
Camera-ready due: July 1, 2015
Registration: July 1, 2015

Call for paper

Data mining has the power to advance different domain problems solving as a scientific and engineering discipline. Various data including textual, multimedia, usage records/logs and social interaction data, sourced from different parties are studied in order to mine knowledge, track interesting targets or figure out relationships from them. However, these massive, heterogeneous and non-synchronous data introduce significant challenges to the data, text, web, and social network mining, for example, generic data modeling and massive data process. How to achieve efficient, accurate, trustworthy, distributed and parallel mining results has become crucial of importance that significantly impacts future success of applications benefited from data mining and its intelligence.

In recent years, data, text, web, and social network mining (DTWSM) has been paid an increasing attention and gained serious studies towards being successfully applied in the practice of the data incentive applications and services. This workshop will continue the success of IEEE DTWSM 2014 (September 11^th 2014, Xi’an, China, held in conjunction with IEEE CIT2014) and invite proposals for contributed talks and demonstrations that highlight novel developments in the foundations, infrastructure, applications and implications of heterogeneous data mining. Together, we will continuously explore and discuss the latest academic and industrial research results related to this research area.

Topics of interest include, but are not limited to:

• Theoretic foundations of heterogeneous data mining
• Mining heterogeneous/multi-source data
• Mining RDF graph, graph and network data
• Mining spatial and temporal data
• Mining unstructured and semi-structured data
• Mining social networks
• Mining high dimensional data
• Mining uncertain data
• Mining imbalanced data
• Mining dynamic/streaming data
• Mining scientific data
• Visual data mining
• Opinion mining and sentiment analysis
• Human, domain, organizational and social factors in data mining

Please email inquiries concerning DTWSM2015 to:
Prof.Jun Liu, Email: liukeen@mail.xjtu.edu.cn