Preference Utility algorithm using GPGPU architecture

Che Lun Hung, Hsiao Hsi Wang, Jieh Shan Yeh, Yu Chen Hu, Chun Yuan Lin, Yaw Ling Lin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Nowadays, with the explosive growth of the network technologies many new applications and services have been developed on Internet. World Wide Web can provide these services provided without the limitation of time and location. Obviously, the number of user is dramatically increasing from amount of the visitations of web pages. In our previous work, we proposed an algorithm to discover more significant information from visited web pages to provide this information to web designers or policy makers to adjust the presentation of their Web contents. However, this algorithm is time-consuming approach due to it needs to scan the whole database many times. Therefore, we propose a GPGPU-based Preference Utility algorithm to enhance the performance by GPGPU parallel model. The proposed algorithm is developed on NVIDIA CUDA architecture. The experimental results show that the proposed method can achieve about 7x times over CPU-based method. The proposed algorithm can used to mine the information from web log data efficiently.

Original languageEnglish
Title of host publication2013 IEEE/ACIS 12th International Conference on Computer and Information Science, ICIS 2013 - Proceedings
Pages155-160
Number of pages6
DOIs
StatePublished - 2013
Event2013 IEEE/ACIS 12th International Conference on Computer and Information Science, ICIS 2013 - Niigata, Japan
Duration: 16 06 201320 06 2013

Publication series

Name2013 IEEE/ACIS 12th International Conference on Computer and Information Science, ICIS 2013 - Proceedings

Conference

Conference2013 IEEE/ACIS 12th International Conference on Computer and Information Science, ICIS 2013
Country/TerritoryJapan
CityNiigata
Period16/06/1320/06/13

Keywords

  • Data mining
  • GPGPU
  • Preference utility
  • Web mining

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