A Parallel Platform for Web Text Mining

作     者：Ping Lu Zhenjiang Dong Shengmei Luo Lixia Liu Shanshan Guan Shengyu Liu Qingcai Chen 

作者机构：ZTE Corporation Shenzhen Graduate SchoolHarbin Institute of Technology 

出 版 物：《ZTE Communications》 (中兴通讯技术（英文版）)

年 卷 期：2013年第11卷第3期

页      面：56-61页

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 

主　　题：natural language processing text mining massive data paral-lel web knowledge service 

摘      要：With user-generated content, anyone can De a content creator. This phenomenon has infinitely increased the amount of information circulated online, and it is beeoming harder to efficiently obtain required information. In this paper, we describe how natural language processing and text mining can be parallelized using Hadoop and Message Passing Interface. We propose a parallel web text mining platform that processes massive amounts data quickly and efficiently. Our web knowledge service platform is designed to collect information about the IT and telecommunications industries from the web and process this in-formation using natural language processing and data-mining techniques.