Relevance search in heterogeneous networks

Conventional research on similarity search focuses on measuring the similarity between objects with the same type. However, in many real-world applications, we need to measure the relatedness between objects with different types. For example, in automatic expert profiling, people are interested in finding the most relevant objects to an expert, where the objects can be of various types, such as research areas, conferences and papers, etc. With the surge of study on heterogeneous networks, the relatedness measure on objects with different types becomes increasingly important. In this paper, we study the relevance search problem in heterogeneous networks, where the task is to measure the relatedness of heterogeneous objects (including objects with the same type or different types). We propose a novel measure, called HeteSim, with the following attributes: (1) a path-constrained measure: the relatedness of object pairs are defined based on the search path that connect two objects t...

• Type: Journal
• Year: 2012
• Where: EDBT
• Authors: Chuan Shi, Xiangnan Kong, Philip S. Yu, Sihong Xie, Bin Wu
• Keywords: Conventional Measures, Database, EDBT 2012, Relevance Search, Similarity Search