A Novel Method on Information Recommendation via Hybrid Similarity
提出一种结合语义相似度的新方法，解决现有链接相似度方法忽略语义信息、计算不准确的问题，适用于网页、论文、社交网络等对象的相似度计算。
Link similarity is widely applied in measuring the similarity between such objects as Web pages, scientific papers, and social networks. However, there are some deficiencies in the existing methods to measure it. For example, they cannot handle some semantic-similar contents. Their computation may not lead to accurate results in some cases. This paper presents a novel method to do so. It introduces the semantic similarity to calculate the similarity between two given objects, and overcomes the drawback caused by the fact that the existing methods ignore the semantic information of objects. It also gives a novel computation function to make the computing result of similarity more accurate.