DocumentCode :
2919869
Title :
An intelligent network user behavior analysis system based on collaborative Markov model and distributed data processing
Author :
Tao Wu ; Hui He ; Xiqian Gu ; Ying Peng ; Yi Zhang ; Yuntao Zhou ; Senzhe Xu
Author_Institution :
Sch. of Software Eng., HUST, Wuhan, China
fYear :
2013
fDate :
27-29 June 2013
Firstpage :
221
Lastpage :
228
Abstract :
With the boom of internet and ecommerce, increasing numbers of people are getting accustomed to online shopping. Consequently, the analysis of network user behavior is of vital importance to the growth of internet enterprise business. In this paper, an intelligent network user behavior analysis system is illustrated based on collaborative Markov model and distributed data processing. As Markov recommendation algorithm is accurate in prediction, it could be able to solve a series of typical problems like cold start to analyze user behavior data after improving by Slope One algorithm compared with the traditional model. Moreover, distributed computing could divide one problem into multiple tasks and share numerous resources. It could process massive data effectively. Therefore, users would acquire the resources which they truly need among massive data conveniently.
Keywords :
Internet; Markov processes; distributed processing; electronic commerce; recommender systems; Internet; Internet enterprise business; Markov recommendation algorithm; collaborative Markov model; distributed data processing; e-commerce; intelligent network user behavior analysis system; online shopping; slope one algorithm; Analytical models; Collaboration; Data models; Distributed databases; Markov processes; Probability; Servers; Collaborative Markov model; Distributed; Prediction; User behavior analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Supported Cooperative Work in Design (CSCWD), 2013 IEEE 17th International Conference on
Conference_Location :
Whistler, BC
Print_ISBN :
978-1-4673-6084-5
Type :
conf
DOI :
10.1109/CSCWD.2013.6580966
Filename :
6580966
Link To Document :
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