Research on Intelligent Perception Algorithm for Sensitive Information

Abstract

In the big data era, a tremendous volume of electronic documents is transmitted via the network, many of which include sensitive information about the country and businesses. There is a pressing need to be able to perform intelligent sensing of sensitive information on these documents in order to be able to discover and guarantee the security of sensitive information in this enormous volume of documents. Although the low effectiveness of manual detection is resolved by the current method of handling sensitive information, there are still downsides, such as poor processing effects and slow speed. This study creatively proposes the Text Sensitive Information Intelligent Perception algorithm (TSIIP), which detects sensitive words at the word level and sensitive statements at the statement level to obtain the final assessment score of the text. We experimentally compare this algorithm with other methods on an existing dataset of sensitive Chinese information. We use the metrics measuring the accuracy of the binary classification model, where the F1 score reaches 0.938 (+0.6%), and the F2 score reaches 0.946 (+1%), and the experimental results fully demonstrate the superiority of this algorithm.

Research on commodity intelligent recommendation system based on data mining

“…Intelligent recommendation algorithm is an algorithm process that forms real-time recommendation results on real-time data based on a large amount of behavioral data 6 between the user and the content based on the content description information 7 . The latter regards the user as a one-dimensional vector, with preference as the term, and uses distance to represent similarity 8 .…”