中文摘要：

开放知识网络中概念语义关联度计算是一个重要的问题．吸取蚁群算法思想中的信息素策略，并以融入了该策略的随机游走作为关联度计算的基本框架，将信息素分布作为语义关联紧密程度的判定依据，提出一种基于随机游走的语义关联度计算方法，以显性方式呈现语义关联度的计算探索过程．该算法主要包含路径选择模型（PSM）和语义关联度计算模型（SRCM）两部分．PSM用于指定游走代理在游走过程中的路径选择、信息素释放过程；SRCM利用游走代理反馈的信息进行语义关联度的计算．实验结果表明，该算法能够在线性复杂度下实现语义关联度的计算，扩展了语义关联度计算的可行策略．

英文摘要：

The semantic relatedness calculation of open domain knowledge network is a significant issue. In this paper, pheromone strategy is drawn from the thought of ant colony algorithm and is integrated into the random walk which is taken as the basic framework of calculating the semantic relatedness degree. The pheromone distribution is taken as a criterion of determining the tightness degree of semantic relatedness. A method of calculating semantic relatedness degree based on random walk is proposed and the exploration process of calculating the semantic relatedness degree is presented in a dominant way. The method mainly con- tains Path Select Model（PSM） and Semantic Relatedness Computing Model（SRCM）. PSM is used to simulate the path selection of ants and pheromone release. SRCM is used to calculate the semantic relatedness by utilizing the information returned by ants. The result indicates that the method could complete semantic relatedness calculation in linear complexity and extend the feasible strategy of semantic relatedness calculation.