Title
BC-PDM: data mining, social network analysis and text mining system based on cloud computing
Abstract
Telecom BI(Business Intelligence) system consists of a set of application programs and technologies for gathering, storing, analyzing and providing access to data, which contribute to manage business information and make decision precisely. However, traditional analysis algorithms meet new challenges as the continued exponential growth in both the volume and the complexity of telecom data. With the Cloud Computing development, some parallel data analysis systems have been emerging. However, existing systems have rarely comprehensive function, either providing data analysis service or providing social network analysis. We need a comprehensive tool to store and analysis large scale data efficiently. In response to the challenge, the SaaS (Software-as-a-Service) BI system, BC-PDM (Big Cloud-Parallel Data Mining), are proposed. BC-PDM supports parallel ETL process, statistical analysis, data mining, text mining and social network analysis which are based on Hadoop. This demo introduces three tasks: business recommendation, customer community detection and user preference classification by employing a real telecom data set. Experimental results show BC-PDM is very efficient and effective for intelligence data analysis.
Year
DOI
Venue
2012
10.1145/2339530.2339764
KDD
Keywords
Field
DocType
data mining,traditional analysis algorithm,text mining system,cloud computing,statistical analysis,intelligence data analysis,real telecom data,telecom data,parallel data analysis system,data analysis service,analysis large scale data,social network analysis,software as a service,business intelligence,text mining,exponential growth,data analysis
Data science,Data mining,Text mining,Data stream mining,Business information,Computer science,Social network analysis,Software as a service,Business intelligence,Data access,Database,Cloud computing
Conference
Citations 
PageRank 
References 
12
1.00
3
Authors
7
Name
Order
Citations
PageRank
Le Yu114412.35
Jian Zheng2121.00
Wei Chong Shen3121.00
Bin Wu459248.75
Bai Wang549652.78
Qian Long65710.30
Bo Ren Zhang7121.00