面向功能语义增强与标签关联的Web服务标签推荐  

Label recommendation of Web services based on functional semantic enhancement and label association

作　　者：刘庆雪 王荔芳 潘国庆 胡强[2] Liu Qingxue;Wang Lifang;Pan Guoqing;Hu Qiang(School of Mechanical&Electrical Engineering,Kunming University,Kunming 650214,China;College of Information Science&Techno-logy,Qingdao University of Science&Technology,Qingdao Shandong 266061,China)

机构地区：[1]昆明学院机电工程学院,昆明650214 [2]青岛科技大学信息科学技术学院,山东青岛266061

出　　处：《计算机应用研究》2024年第9期2678-2684,共7页Application Research of Computers

基　　金：国家自然科学基金资助项目(61973180);云南省科技厅资助项目(202305AO350007,202305AP350017);云南省地方本科高校基础研究联合专项面上项目(202301BA070001-003,202001BA070001-197,202001BA070001-173);昆明学院引进人才项目(YJL2205);云南省昆明市院士专家工作站项目(YSZJGZZ-2022099);山东省重点研发计划软科学项目(2023RKY01009)。

摘　　要：为了提升标签推荐的质量,提出一种面向功能语义增强与标签关联的Web服务标签推荐方法。将语境权重融入TextRank模型,提取与服务功能契合度高的关键词,用于构建功能语义增强的服务表征向量;建立标签关联图,基于改进的GraphSAGE模型生成标签关联向量;利用KNN算法获取推荐的主标签与候选标签集合,面向服务表征向量和标签关联向量构建融合适配度与关联度的标签推荐方法。实验表明,所提方法在accuracy与F_(1)-score指标上优于当前流行的标签推荐方法,标签推荐质量得到提升。To improve the quality of label recommendation,this paper proposed a label recommendation method for Web services oriented functional semantic enhancement and label association.It integrated the context weight into the TextRank model to extract keywords that fitted well with the service function,which were used to construct the functional semantic enhanced service representation vector.It established the label association graph and generated the label association vector based on the improved GraphSAGE model.It used the KNN algorithm to obtain the recommended primary label and candidate label set.It used the service representation vector and label association vector to construct a label recommendation method combining fitness and association.Experiments show that the proposed method is superior to the current popular label recommendation methods in terms of accuracy and F_(1)-score,and it improves the quality of tag recommendation.

关 键 词：WEB服务 语境权重 语义增强 标签关联 标签推荐 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]