Effective Recommendations based on Multi-Source Data

从Web、传感器网络、学术出版物和社交网络等多个来源收集的大规模数据提供了一个新的机会，可以利用有用的信息进行有效和高效的建议和决策。该项目将提出一个新的推荐系统框架，该框架基于分析来自多个数据源的不同类型对象之间的关系。将建立一个图模型来表示提取的语义关系和新的链接分析为基础的算法将开发对象的排名。该项目的结果将支持许多关键应用，如医疗保健。

Large-scale data collected from multiple sources such as the Web, sensor networks, academic publications, and social networks provide a new opportunity to exploit useful information for effective and efficient recommendations and decision making. The project will propose a new framework of recommender systems that is based on analysing relationships between different types of objects from multiple data sources. A graph model will be built to represent the extracted semantic relationships and novel linkage-analysis based algorithms will be developed for ranking objects. The results from this project will underpin many critical applications such as healthcare.