Mining Knowledge from Data: An Information Network Analysis Approach

Abstract—Most objects and data in the real world are interconnected, forming complex, heterogeneous but often semistructured information networks. However, many database researchers consider a database merely as a data repository that supports storage and retrieval rather than an information-rich, inter-related and multi-typed information network that supports comprehensive data analysis; whereas many network researchers focus on homogeneous networks. Departing from both, we view interconnected, semi-structured datasets as heterogeneous, information-rich networks and study how to uncover hidden knowledge in such networks. For example, a university database can be viewed as a heterogeneous information network, where objects of multiple types, such as students, professors, courses, departments, and multiple typed relationships, such as teach and advise are intertwined together, providing abundant information. In this tutorial, we present an organized picture on mining heterogeneous inf...

• Type: Journal
• Year: 2012
• Where: ICDE
• Authors: Jiawei Han, Yizhou Sun, Xifeng Yan, Philip S. Yu
• Keywords: Database, ICDE 2012, Promising Research Directions, Research Frontiers, Similarity Search