项目名称: 新型社会网络模型及在社会媒体文本摘要和图像标注的应用
项目编号: No.61272240
项目类型: 面上项目
立项/批准年度: 2013
项目学科: 自动化技术、计算机技术
项目作者: 马军
作者单位: 山东大学
项目金额: 80万元
中文摘要: 以微博和共享媒体等组成的社会媒体正日益成为人们获取实时信息的重要来源。但社会媒体上的信息格式、传播方式和信息质量都和传统的静态网页有很多不同,急需新的理论模型和算法。由于社会网络模型可以很好地表示用户之间、文档之间、图像之间、和用户与文档之间各种不同关系,本课题将以社会媒体文本摘要和图像标注为应用背景,研究面向社会媒体信息处理的社会网络模型以及应用。具体包括研究社会网络的动态拓扑进化特性、网络节点的影响力计算及与节点所发送信息质量的关系;如何利用异质社会网络中的不同性质关系合成和节点属性来计算异质网络中的对象相似度,并应用到社区发现和图像标注;研究能反映网络社区中会话型信息流的动态主题模型,并研究如何利用该模型和网络信息质量计算的结果,改善对数据流形式的文本摘要。该研究的目标是基于社会媒体信息处理的视角,探索新型社会网络,并应用到更多的社会媒体信息处理应用中。
中文关键词: 推荐系统;图像标注;复杂网络分析;主题模型;机器学习
英文摘要: Social media,consisting of microblogging, media sharing platforms and so on, are rapidly becoming the important information source for people to access real-time information. However, there is great difference between the information in social media and in traditional web sites in terms of the information formats, the ways of propagation and quality of information. Therefore new theoretical models and algorithms are urgently needed. Since social network models can be used to describe various kinds of relationships between users and users, documents and documents, images and images as well as users and documents in social media, in this application project we want to study the social media information processing oriented social networks and their applications under the application backgrounds of multi-document summarization and image annotation. The research refer to following issues: the features of the dynamic evolution of social networks; the influence of the users in the social networks and the relation with the qualities of the message sent by the users; new similarity measure on two objects in heterogeneous social networks based on the different kinds of relation compositions and the attributes of users, and how to apply the similarity computation to discover different network societies and annotate images
英文关键词: recommendation systems;image annotation;the analysis on complexity networks;topic models;machine learning