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Your search keyword '"Xiao, Xiaokui"' showing total 17 results
Start Over Author "Xiao, Xiaokui" Journal ieee transactions on knowledge and data engineering
17 results on '"Xiao, Xiaokui"'

1. Managing Metaverse Data Tsunami: Actionable Insights

Author

Zhang, Bingxue, primary, Chen, Gang, additional, Ooi, Beng Chin, additional, Shou, Mike Zheng, additional, Tan, Kian-Lee, additional, Tung, Anthony K. H., additional, Xiao, Xiaokui, additional, Yip, James Wei Luen, additional, and Zhang, Meihui, additional

Published
2024
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5. ANGEL: enhancing the utility of generalization for privacy preserving publication

Author

Tao, Yufei, Chen, Hekang, Xiao, Xiaokui, Zhou, Shuigeng, and Zhang, Donghui

Subjects
Privacy -- Analysis, Data security -- Methods, Data security -- Reports, Privacy issue, Data security issue, Business, Computers, Electronics, Electronics and electrical industries
Abstract

Generalization is a well-known method for privacy preserving data publication. Despite its vast popularity, it has several drawbacks such as heavy information loss, difficulty of supporting marginal publication, and so on. To overcome these drawbacks, we develop ANGEL, (1) a new anonymization technique that is as effective as generalization in privacy protection, but is able to retain significantly more information in the microdata. ANGEL is applicable to any monotonic principles (e.g., l-diversity, t-closeness, etc.), with its superiority (in correlation preservation) especially obvious when tight privacy control must be enforced. We show that ANGEL lends itself elegantly to the hard problem of marginal publication. In particular, unlike generalization that can release only restricted marginals, our technique can be easily used to publish any marginals with strong privacy guarantees. Index Terms--Privacy, generalization, ANGEL.

Published
2009

7. Efficient skyline and top-k retrieval in subspaces

Author

Tao, Yufei, Xiao, Xiaokui, and Pei, Jian

Subjects
Algorithms -- Usage, Algorithms -- Analysis, Information storage and retrieval -- Analysis, Trees (Graph theory) -- Usage, Trees (Graph theory) -- Analysis, Algorithm, Business, Computers, Electronics, Electronics and electrical industries
Abstract

Skyline and top-k queries are two popular operations for preference retrieval. In practice, applications that require these operations usually provide numerous candidate attributes, whereas, depending on their interests, users may issue queries regarding different subsets of the dimensions. The existing algorithms are inadequate for subspace skyline/top-k search because they have at least one of the following defects: 1) They require scanning the entire database at least once, 2) they are optimized for one subspace but incur significant overhead for other subspaces, or 3) they demand expensive maintenance cost or space consumption. In this paper, we propose a technique SUBSKY, which settles both types of queries by using purely relational technologies. The core of SUBSKY is a transformation that converts multidimensional data to one-dimensional (1D) values. These values are indexed by a simple B-tree, which allows us to answer subspace queries by accessing a fraction of the database. SUBSKY entails low maintenance overhead, which equals the cost of updating a traditional B-tree. Extensive experiments with real data confirm that our technique outperforms alternative solutions significantly in both efficiency and scalability. Index Terms--Skyline, top-k, subspace, B-tree.

Published
2007

10. The Disruptions of 5G on Data-Driven Technologies and Applications

Author

Loghin, Dumitrel, primary, Cai, Shaofeng, additional, Chen, Gang, additional, Dinh, Tien Tuan Anh, additional, Fan, Feiyi, additional, Lin, Qian, additional, Ng, Janice, additional, Ooi, Beng Chin, additional, Sun, Xutao, additional, Ta, Quang-Trung, additional, Wang, Wei, additional, Xiao, Xiaokui, additional, Yang, Yang, additional, Zhang, Meihui, additional, and Zhang, Zhonghua, additional

Published
2020
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