Text Content Filtering Based on Chinese Character Reconstruction from Radicals

Content filtering through keyword matching is widely adopted in network censoring, and proven to be successful. However, a technique to bypass this kind of censorship by decomposing Chinese characters appears recently. Chinese characters are combinations of radicals, and splitting characters into radicals pose a big obstacle to keyword filtering. To tackle this challenge, we proposed the first filtering technology based on combination of Chinese character radicals. We use a modified Rabin-Karp algorithm to reconstruct characters from radicals according to Chinese character structure library. Then we use another modified Rabin-Karp algorithm to filter keywords among massive text content. Experiment shows that our approach can identify most of the keywords in the form of combination of radicals and yields a visible improvement in the filtering result compared to traditional keyword filtering.