Abstract
Conference Title: 2015 IEEE/ACS 12th International Conference of Computer Systems and Applications (AICCSA) Conference Start Date: 2015, Nov. 17 Conference End Date: 2015, Nov. 20 Conference Location: Marrakech, Morocco Frequent subgraph mining is useful in most knowledge discovery tasks such as classification, clustering and indexing. Many algorithms and methods have been developed to mine frequent subgraphs. To have an understanding of several mining frequent subgraph algorithms, it is advantageous to establish a common framework for their study. In this paper, we propose a comparative study of several approaches by focusing on the intrinsic characteristics of these algorithms. A set of existing approaches in literature are reviewed and categorized according to the certainty nature of input which can be exact or uncertain graphs.