东南大学学报（自然科学版）Issue(2)：261-265,5.DOI:10.3969/j.issn.1001-0505.2014.02.007
一种基于多分类语义分析和个性化的语义检索方法
Semantic search approach based on multi-classification semantic analysis and personalization
摘要
Abstract
To further enhance the accuracy of semantic search and improve the user experience,a novel approach for semantic search based on multi-classification semantic analysis (MSA)and per-sonalization is presented.First,documents are transformed into vectors and stored in term vector da-tabase (TVDB )by using the modified MSA method.Then,documents are classified by support vector machine(SVM)and wrote into index with categories.In the search process,users' search history and personal information are used to optimize the search results with the help of TVDB .The experiment results show that the average precision,the average discounted cumulative gain(DCG) and the average normalized discounted cumulative gain(nDCG)otained by using this approach are 0.7,7.267 and 0.890,respectively,which are 31%,36%and 19%higher than the average of the results calculated by the Lucene method and the Yahoo Directory method.And the time complexity per query is 0.669 s,which is only 0.326 s more than that by using the Lucene method.Therefore, this approach can improve the relevance and precision of semantic search with a rational time cost.关键词
语义检索/多分类语义分析/词向量库/个性化算法Key words
semantic search/multi-classification semantic analysis (MSA)/term vector database (TVDB )/personalization algorithm分类
信息技术与安全科学引用本文复制引用
马应龙,李鹏鹏,张敬旭..一种基于多分类语义分析和个性化的语义检索方法[J].东南大学学报（自然科学版）,2014,(2):261-265,5.基金项目
国家自然科学基金资助项目（61001197，61372182）、国家电网公司科技资助项目（522722130292）． （）
