国际语义网会议是介绍有关语义、数据和Web的基础研究、创新技术和应用的主要场所。旨在寻找针对语义Web的理论、分析和经验方面的新颖而重要的研究贡献,也鼓励在语义网和其他科学学科交叉领域的研究上做出贡献。提交到研究内容应该描述语义Web上的原创、有意义和可复制的研究。所有的论文必须包括方法评估,是严格的,可重复和可复制的。 官网地址:http://dblp.uni-trier.de/db/conf/semweb/

Today, Internet is one of the widest available media worldwide. Recommendation systems are increasingly being used in various applications such as movie recommendation, mobile recommendation, article recommendation and etc. Collaborative Filtering (CF) and Content-Based (CB) are Well-known techniques for building recommendation systems. Topic modeling based on LDA, is a powerful technique for semantic mining and perform topic extraction. In the past few years, many articles have been published based on LDA technique for building recommendation systems. In this paper, we present taxonomy of recommendation systems and applications based on LDA. In addition, we utilize LDA and Gibbs sampling algorithms to evaluate ISWC and WWW conference publications in computer science. Our study suggest that the recommendation systems based on LDA could be effective in building smart recommendation system in online communities.

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