Evaluation of Natural Language Processing on Local and Public Cloud Resources

• Item type: SIG Technical Reports(1)
• 公開日: 2010-07-27
• タイトル: Evaluation of Natural Language Processing on Local and Public Cloud Resources
• タイトル / 言語: en
• タイトル: Evaluation of Natural Language Processing on Local and Public Cloud Resources
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: クラウド
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_18gh
• 資源タイプ: technical report
• 著者所属: Tokyo Institution of Technology
• 著者所属: National Institute of Informatics／Tokyo Institution of Technology
• 著者所属(英): en
• 著者所属(英): Tokyo Institution of Technology
• 著者所属(英): en
• 著者所属(英): National Institute of Informatics / Tokyo Institution of Technology
• 著者名: Hao, Sun; Kento, Aida
• 著者名(英): Hao, Sun; Kento, Aida
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: In high-performance computing, parameter survey applications, which consists of a lot of independent tasks with different input parameters are typical and conventionally run on local computing resources with batch scheduler systems such as SGE and Condor. Our targeted PSA application is a Natural Language Processing (NLP) application. It uses Support Vector Machine (SVM) to learn and eliminate abuse words from the commercial bulletin board systems (BBSs) documents. Security issues become important because it processes confidential documents including personal informations. In this paper, we implemented an effective and secure hybrid mechanism with our previous work, InterS. It adds IaaS Cloud resources to the batch schedulers when the local resources are insufficient due to failures or overhead by external application tasks. It utilizes Amazon VPC service to enable the secure computation of our NLP application. InterS run the NLP application in our experiment and the evaluation of time efficiency is shown from the results.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: In high-performance computing, parameter survey applications, which consists of a lot of independent tasks with different input parameters are typical and conventionally run on local computing resources with batch scheduler systems such as SGE and Condor. Our targeted PSA application is a Natural Language Processing (NLP) application. It uses Support Vector Machine (SVM) to learn and eliminate abuse words from the commercial bulletin board systems (BBSs) documents. Security issues become important because it processes confidential documents including personal informations. In this paper, we implemented an effective and secure hybrid mechanism with our previous work, InterS. It adds IaaS Cloud resources to the batch schedulers when the local resources are insufficient due to failures or overhead by external application tasks. It utilizes Amazon VPC service to enable the secure computation of our NLP application. InterS run the NLP application in our experiment and the evaluation of time efficiency is shown from the results.
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AN10463942
• 書誌情報: 研究報告ハイパフォーマンスコンピューティング（HPC）; 巻 2010-HPC-126, 号 40, p. 1-8, 発行日 2010-07-27
• Notice: SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc.
• 出版者 / 言語: ja
• 出版者: 情報処理学会