摘要： 基于重启型随机游走模型和个人化PageRank算法，提出一种新的图上关键字搜索算法。该算法将向量空间模型和随机游走模型进行有效的结合，使查询搜索得到的结果可以匹配查询关键字，通过充分挖掘利用图中隐含的结构信息，更好地提供搜索结果。实验结果证明了该算法的有效性。

关键词:

font-family: 华文中宋, mso-ascii-font-family: 'Times New Roman', mso-hansi-font-family: 'Times New Roman'">关键字搜索, 随机游走, 重启型随机游走模型, 向量空间模型

Abstract: This paper presents a new keyword search on graphs algorithm based on random walk with restart model and personalized PageRank algorithm. By combining vector space model and random walk model effectively, it can make the results match the query keywords as well as the structural information implied in the graph, which provides better searching results. Experimental result proves that the algorithm is effective.

Key words: keyword search, random walk, random walk with restart model, vector space model

中图分类号: 

• TP311.13