HeteSim: A General Framework for Relevance Measure in Heterogeneous Networks
HeteSim: A General Framework for Relevance Measure in Heterogeneous Networks
复制标题
HeteSim：异构网络中相关性测量的通用框架
DOI：
10.1109/tkde.2013.2297920
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发表时间：
2014-10-01
影响因子：
8.9
通讯作者：
Wu, Bin
中科院分区：
文献类型：
--
作者：
Shi, Chuan;Kong, Xiangnan;Wu, Bin
相似度搜索是许多应用程序中的一个重要功能，它通常侧重于测量具有相同类型的对象之间的相似度。然而，在许多场景中，我们需要度量不同类型对象之间的相关性。随着异构网络研究的兴起，对不同类型对象的关联度量变得越来越重要。本文研究了异构网络中的关联搜索问题，其任务是度量异构对象（包括相同类型或不同类型的对象）的相关性。提出了一种新的度量HeteSim，它具有以下属性：(1)统一度量：它可以在统一的框架内度量相同或不同类型对象的相关性；(2)路径约束度量：根据节点类型序列连接两个对象的搜索路径定义对象对的相关性；(3)半度量：HeteSim具有一些很好的性质（如自极大和对称），这对许多数据挖掘任务至关重要。分析了HeteSim的计算特点，提出了相应的快速计算策略。实证研究表明，HeteSim能够有效、高效地评价异构对象的相关性。
Similarity search is an important function in many applications, which usually focuses on measuring the similarity between objects with the same type. However, in many scenarios, we need to measure the relatedness between objects with different types. With the surge of study on heterogeneous networks, the relevance 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). A novel measure HeteSim is proposed, which has the following attributes: (1) a uniform measure: it can measure the relatedness of objects with the same or different types in a uniform framework; (2) a path-constrained measure: the relatedness of object pairs are defined based on the search path that connects two objects through following a sequence of node types; (3) a semi-metric measure: HeteSim has some good properties (e.g., selfmaximum and symmetric), which are crucial to many data mining tasks. Moreover, we analyze the computation characteristics of HeteSim and propose the corresponding quick computation strategies. Empirical studies show that HeteSim can effectively and efficiently evaluate the relatedness of heterogeneous objects.