基于微博引用的个性化推荐
Personalized Recommendation Based on Micro-blogging References
本文提出了一种基于微博引用及其用户特征和分类的协同过滤推荐算法，该算法综合考虑了微博用户信息及习惯特征和用户引用内容分类偏好特征的相似性。对于微博个性化推荐中的用户运算数据集的选取，本文提出了基于用户关系的用户数据集抽取和基于分类特征的用户数据集抽取的方法，对算法的性能有很大的提升和优化。
microblogging reference and user features & category based algorithm is proposed. The algorithm joins the reference category and user features similarity to user's similarity calculating. In order to select the computing users' set of microblogging personalized recommendation, a data extraction method based on users' relationship and category feature is proposed. Thus simplifying the number of computing set greatly, and the performance of algorithm has been optimized greatly.
林雪能、陈光、邹扬、朱帅
通信
自然语言处理个性化推荐协同过滤特征抽取
Natural Language ProcessingPersonalized RecommendationCollaborative FilteringFeature Extraction
林雪能,陈光,邹扬,朱帅.基于微博引用的个性化推荐[EB/OL].(2012-12-28)[2025-08-23].http://www.paper.edu.cn/releasepaper/content/201212-1076.点此复制
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