文献类型：期刊文献

中文题名：Istraivanje modela izluivanja mrenih informacija utemeljenog na poboljanoj tehnologiji tematski usmjerenog pretraivaa

英文题名：RESEARCH ON MODEL OF NETWORK INFORMATION EXTRACTION BASED ON IMPROVED TOPIC-FOCUSED WEB CRAWLER KEY TECHNOLOGY

作者：Chen, Mo[1,2];Yang, Xiao-Ping[1]

第一作者：陈默;Chen, Mo

通讯作者：Chen, M[1];Chen, M[2]

机构：[1]Renmin Univ China, Sch Informat, Beijing 100872, Peoples R China;[2]Beijing Union Univ, Coll Business, Beijing 100025, Peoples R China

第一机构：Renmin Univ China, Sch Informat, Beijing 100872, Peoples R China

通讯机构：[1]corresponding author), Renmin Univ China, Sch Informat, Beijing 100872, Peoples R China;[2]corresponding author), Beijing Union Univ, Coll Business, Beijing 100025, Peoples R China.|[1141721]北京联合大学商务学院;[11417]北京联合大学;

年份：2016

卷号：23

期号：4

起止页码：1025-1035

外文期刊名：TEHNICKI VJESNIK-TECHNICAL GAZETTE

收录：;EI(收录号：20163402736094);WOS:【SCI-EXPANDED(收录号:WOS:000382353400014)】；

基金：This work was supported by the National Natural Science Foundation of China under Grant Nos. 71271209, the project of science and technology plan of Beijing Education Committee under Grant Nos. KM201311417011, Funding Project for Academic Human Resources Development in Beijing Union University under Grant Nos. BPHR2012A02, the project of Philosophy and Social Science Planning of Beijing Nos. 13JGC090, and the project of a new starting point in Beijing Union University.

语种：英文

外文关键词：network information extraction; relativity calculation; search strategy; topic-focused web crawler

摘要：This research has caught researchers' wide attention for extracting network information exactly with the arrival of the big data era characterized by semi structured or unstructured text. This paper proposes a model of network information extraction based on improved topic-focused web crawler key technology taking Web news as object of extraction. The authors elaborate main function, method and technology on every layer of the model in detail, which have been used or completed, and focuses on how to extract network information efficiently oriented topic from a large number of Web news instances, in order to explore a research method for network information extraction. The experimental results show the feasibility, validity and superiority of the model design and play a very important role in constructing topic-focused Web news corpus so as to provide a real-time data source for trust analysis, currency analysis, hot topic detection, topic evolution tracking of Web news.