关键词: 领域概念获取, 改进近邻传播算法, 对数似然比, 语义相似度, 互信息

Abstract: For statistical method lacks semantic information between words in domain concepts extraction, this paper presents a domain concept automatic extraction method, which combines semantic similarity and improved affinity propagation. The compound words are extracted by using mutual information, and then the log-likelihood is used to avoid the omission of low-frequency words, after that the synonyms between terms are identified by using HowNet and the cosine similarity. The improved affinity propagation algorithm is used to obtain the collection of domain concepts. The experimental results show that the method has higher accuracy, recall rate, and perplexity change ratio than the traditional method.

Key words: domain concept extraction, improved affinity propagation, log-likelihood, semantic similarity, mutual information