A Survey of Frequent Subtrees and Subgraphs Mining Methods
Hamed Dinari, Hassan Naderi · International Journal of Computer Science and business informatics/International journal of computer science and business informatics · 2014
A graph is a basic data structure which, can be used to model complex structures and the relationships between them, such as XML documents, social networks, communication networks, chemical informatics, biology networks, and structure of web pages. Frequent subgraph pattern mining is one of the most important fields in graph mining. In light of many applications for it, there are extensive researches in this area, such as analysis and processing of XML documents, documents clustering and classification, images and video indexing, graph indexing for graph querying, routing in computer networks, web links analysis, drugs design, and carcinogenesis. Several frequent pattern mining algorithms have been proposed in recent years and every day a new one is introduced. The fact that these algorithms use various methods on different datasets, patterns mining types, graph and tree representations, it is not easy to study them in terms of features and performance. This paper presents a brief report of an intensive investigation of actual frequent subgraphs and subtrees mining algorithms. The algorithms were also categorized based on different features.