基于用户交互行为挖掘的个性化图像标签推荐研究

项目名称： 基于用户交互行为挖掘的个性化图像标签推荐研究

项目编号： No.61303090

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 自动化技术、计算机技术

项目作者： 刘峥

作者单位： 山东财经大学

项目金额： 23万元

中文摘要： 实现个性化搜索是下一代图像搜索引擎的目标，其关键问题是为图像赋予既符合用户兴趣又能有效描述图像视觉内容的标签，即个性化图像标签推荐，进而利用成熟的文本检索技术实现简单高效的个性化图像检索。本项目以图像共享社区为应用背景，以用户之间的交互行为挖掘为切入点，研究个性化图像标签推荐方法。首先，通过模糊综合评价量化用户交互度，构造用户交互图；其次，以目标用户为约束条件，实现面向目标用户并支持增量扩展的社区发现算法；再次，通过改进的主题模型融合图像的各种元数据，求得用户兴趣的主题概率分布和各主题的时间分布，用层次向量空间模型将用户兴趣表示为"用户兴趣向量"；最后，以图像的视觉特征和目标用户的兴趣向量为先验条件，利用贝叶斯定理将候选标签库中具有最大后验概率的标签推荐给目标用户。本项目的实施，将对多媒体信息检索和社会网络数据挖掘的基础理论研究起到推动作用，为下一代图像检索系统提供核心算法与关键技术。

中文关键词： 在线社会网络；用户兴趣建模；个性化推荐；图像标签；语义挖掘

英文摘要： Achieving personalized search is the goal of the next-generation image search engine, of which the key problem is to give the image some tags that can not only meet user interests but also effectively describe image visual contents, that is, personalized image tag recommendation. Afterwards, a simple and efficient personalized image retrieval system can be implemented by taking advantage of the mature text retrieval technology. This project regards the image sharing community as application background, and considers user interaction behavior mining as the breakthrough point. Furthermore, the aim of this project is to study on an effective method of personalized image tag recommendation. Firstly, fuzzy synthetic evaluation is utilized to quantify the degree of user interaction and then user interaction graph is constructed. Secondly, the target user oriented community discovery which supports incremental expansion is implemented by considering the target user as constraints. Thirdly, all kinds of image metadata are fused by a modified topic model, and then the topic probability distribution of user interest and the time distribution of each topic are obtained. Hence, the user interest vector is constructed by a hierarchical vector space model based on the above two distributions. Finally, adopting image visual fe

英文关键词： Online Social Network；User Interest Modeling；Personalized Recommendation；Image Tag；Semantic Mining