Graph based data representation offers a convenient possibility to represent entities, their attributes, and their relationships to other entities. Consequently, the use of graph based representation for data mining has become a promising approach to extracting novel and useful knowledge from relational data. In order to check whether a certain graph occurs, as a substructure, within a larger d...

Mining maximal frequent itemsets is very important in many data mining applications. How to improve the efficiency and effectiveness of mining algorithm has become an interesting issue in the world. In this paper, we introduce a new method to solve this problem, which is based on graph theory. Firstly, the concept of directed itemsets graph and the trifurcate linked list storage structure are p...

In NTCIR-10, we participated in the subtask of Subtopic Mining. We classify test topics into two types: role-explicit topic and roleimplicit topic. According to the topic type, we devise different approaches to perform subtopic mining. Specifically, for roleexplicit topics, we propose an approach of modifier graph based subtopic mining. The key idea is that: The modifier graph corresponding to ...

Graph theoretical ideas are highly utilized by computer science fields especially data mining. In this field, a data structure can be designed in the form of tree. Covering is a widely used form of data structure in data mining and covering-based rough sets provide a systematic approach to this type of data. In this paper, we study the connectedness of graphs through covering-based rough sets a...

The prosperity of Web 2.0 and social media brings about many diverse social networks of unprecedented scales, which present new challenges for more effective graph-mining techniques. In this chapter, we present some graph patterns that are commonly observed in large-scale social networks. As most networks demonstrate strong community structures, one basic task in social network analysis is comm...

Association rule mining is a function of data mining research domain and frequent pattern mining is an essential part of it. Most of the previous studies on mining frequent patterns based on an Apriori approach, which required more number of database scans and operations for counting pattern supports in the database. Since the size of each set of transaction may be massive that it makes difficu...