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An Efficient Algorithm for Diversified Top-k Subgraph Querying
http://doi.org/10.5626/JOK.2024.51.2.103
Subgraph matching is a core and important problem in graph analysis. The subgraph matching problem is to find all embeddings of the query graph in the data graph. However, the output results from previously proposed algorithms often overlap with each other, and thus interesting results are often missed. For this purpose, the diversified top-k subgraph querying problem is proposed. The diversified top-k subgraph querying problem is to find k embeddings that have the highest coverage among embeddings of the query graph in the data graph. In this paper, we present an algorithm for the diversified top-k subgraph querying problem and demonstrate that it finds diversified top-k results efficiently compared to existing algorithms.
A Study on Service-based Secure Anonymization for Data Utility Enhancement
Chikwang Hwang, Jongwon Choe, Choong Seon Hong
Personal information includes information about a living human individual. It is the information identifiable through name, resident registration number, and image, etc. Personal information which is collected by institutions can be wrongfully used, because it contains confidential information of an information object. In order to prevent this, a method is used to remove personal identification elements before distributing and sharing the data. However, even when the identifier such as the name and the resident registration number is removed or changed, personal information can be exposed in the case of a linking attack. This paper proposes a new anonymization technique to enhance data utility. To achieve this, attributes that are utilized in service tend to anonymize at a low level. In addition, the anonymization technique of the proposal can provide two or more anonymized data tables from one original data table without concern about a linking attack. We also verify our proposal by using the cooperative game theory.
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