Original scientific paper

https://doi.org/10.17559/TV-20150314134638

Research on model of network information extraction based on improved topic-focused Web crawler key technology

Mo Chen ; School of Information, Renmin University of China, Beijing 100872, China
Xiao-Ping Yang ; School of Information, Renmin University of China, Beijing 100872, China

Abstract

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.

Keywords

network information extraction; relativity calculation; search strategy; topic-focused web crawler

Hrčak ID:

163814

URI

https://hrcak.srce.hr/163814

Publication date:

16.8.2016.

Article data in other languages: croatian

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