Reachability vectors: features for link-based similarity measures

Seok-Ho Yoon, Ji-Soo Kim, Jiwoon Ha, Sang-Wook Kim, Minsoo Ryu, Ho‐Jin Choi
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Abstract

In this paper, we present a novel approach to computing link-based similarities among objects accurately. We discuss the problems with previous link-based similarity measures and propose a novel approach that does not suffer from these problems. In the proposed approach, each target object is represented by a vector. The elements of the vector denote all the objects in the given data set, and the value of each element indicates the weight of the corresponding object with respect to the target object. As for this weight value, we propose to utilize the probability of reaching from the target object to the specific object, computed using the "Random Walk with Restart" strategy. Then, we define the similarity between two objects as the cosine similarity of the two vectors representing the two objects. We also evaluate the performance of the proposed approach in comparison with existing link-based measures using two kinds of data sets. Our experimental results show that the proposed approach significantly outperform the existing measures.
可达性向量:基于链接的相似性度量的特征
在本文中,我们提出了一种新的方法来精确计算基于链接的对象之间的相似度。我们讨论了以前基于链接的相似度度量的问题,并提出了一种不受这些问题影响的新方法。在提出的方法中,每个目标对象由一个向量表示。向量的元素表示给定数据集中的所有对象,每个元素的值表示对应对象相对于目标对象的权重。对于这个权重值,我们建议利用从目标对象到达特定对象的概率,使用“随机行走与重启”策略计算。然后,我们将两个对象之间的相似度定义为表示两个对象的两个向量的余弦相似度。我们还使用两种类型的数据集与现有的基于链路的度量方法进行比较,评估了所提出方法的性能。实验结果表明,所提出的方法明显优于现有的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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