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Enterprises and governments around the world have been attempting to leverage intelligence from the community by making formally in-house database available to the public for analyzing. The released data was often "anonymized": sensitive attributes were removed from the dataset for privacy protection. However it is proved that masking sensitive attributes alone is not adequate for data protection...
This paper aims at the main problem of existing online teaching platform about lack of interaction and explores the construction and application of the SPOC (Small Private Online Course) online learning platform. The design and implementation of the SPOC platform based on Tencent Cloud are introduced from the technical level. On this basis, teaching practice and exploration in SPOC mode including...
Web security evaluation is an important way for resolving Web security. This paper introduces the commonly used Web security comprehensive evaluation tools. Application examples and the comparison of their abilities are also given. Some inherent flaws in these tools which use the completely automatic method are analyzed. On this basis, we integrate black box and white box testing and propose a generic...
Inspired by the great success of information retrieval (IR) style keyword search on the Web, keyword search on XML has emerged recently. The difference between text database and XML database results in three new challenges: (1) Identify the user search intention, i.e. identify the XML node types that user wants to search for and search via. (2) Resolve keyword ambiguity problems: a keyword can appear...
Discovering maximum frequent item sets is a key problem in data mining. In order to overcome the deficiencies of apriori-like algorithms which adopt candidate itemsets generation-and-test approach, we propose a new algorithm ML_DMFIA which based on DMFIA to mine maximum frequent itemsets in multiple-level association rules. ML_DMFIA utilizes FP-tree structure and up-down progressive deepening searching...
This paper proposes a self-constructed Mercer kernel based subspace LDA approach for face recognition. Our self-constructed Mercer (SM) kernel function is constructed from a given block diagonal matrix. The entries of all its block diagonal sub-matrices are equal to 1. It shows that this kind of matrix is a symmetric, positive semi-definite matrix and thus can serve as a kernel matrix. Based on such...
Discovering maximum frequent itemsets is a key issue in data mining applications. Most of the previous studies adopt an Apriori-like candidate itemsets generation-and-test approach, however, candidate itemsets generation is costly. In this study, we propose a new algorithm named ML_Pincer for discovering maximum frequent itemsets in multiple-level association rules. ML_Pincer algorithm combines the...
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