Hong Jiang
ABSTRACT
With the development of the Internet and news media, numerous information releasing websites are emerging one after another, and the importance of website content supervision is also increasing day by day. Due to the convenience of the Internet, the speed of public opinion dissemination and fermentation is extremely fast. If only relying on manual monitoring, it is difficult to detect problems at the first time. Most of the existing sensitive word detection solutions probe sensitive words in the website when the content is published, but the sensitive words will be changing with current events, and the detection at the time of content publishing can no longer meet the needs of public opinion monitoring. In order to improve the efficiency of sensitive word detection, the advantages of two deterministic finite automata (DFA) algorithms (AC and DAT) are combined in this paper, and an improved multi-pattern string matching algorithm (IQAT, Improved Quad-Array Trie) is presented. The empirical results demonstrate that the proposed algorithm substantially improves the detection performance and memory consumption over existing methods.
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Index Terms
- An Improved Quad-Array Trie Algorithm for Website Sensitive Word Detection
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