辽宁工程技术大学学报（自然科学版）2024，Vol.43Issue(2)：241-247,7.DOI:10.11956/j.issn.1008-0562.2024.02.016
基于混合兴趣主题模型的推荐方法
A recommendation method based on mixed interest topics model
摘要
Abstract
To solve the cold start problem caused by user interest sparsity in cross-area project recommendation,this paper proposes a recommendation method on mixed interest topic model PA-LDA.PA-LDA uses the P-LDA module,which generates the interest topic distribution to target project by mining users'historical behavior data.Then P-LDA employs conduct parameter estimation to build model by the interaction between the topics and the content words,which helps to measure the users'interest on the target project.PA-LDA uses A-LDA module to measure the area interest on the target project.PA-LDA employs top-k method to recommend the target project based on the result of the two mixed interest measurements.The effectiveness and efficiency of our method are verified by experiments on two real data sets EdX and GCSE.The research can effectively explain the principles of effect on recommendation by user interest and domain interest.It also realizes the interest feature capture in multi-dimensional area recommendation,which improves the adaptability and accuracy of recommendation.关键词
主题模型/用户兴趣/领域兴趣/兴趣混合/top-k推荐Key words
topic model/user interest/area interest/interest fusion/top-k recommendation分类
信息技术与安全科学引用本文复制引用
邱云飞,田丰维..基于混合兴趣主题模型的推荐方法[J].辽宁工程技术大学学报（自然科学版）,2024,43(2):241-247,7.基金项目
国家自然科学基金项目(71771111) （71771111）
