个性化图像检索中用户兴趣模型的构建方法  

Constructing user preference profile in personalized image retrieval

作　　者：贺琳[1] 张菁[1] 沈兰荪[1] 

机构地区：[1]北京工业大学信号与信息处理研究室,北京100124

出　　处：《计算机工程与应用》2009年第31期168-171,共4页Computer Engineering and Applications

基　　金：国家自然科学基金No.60472036;No.60431020;No.60402036;北京市自然科学基金No.3052005;No.4062006;教育部博士点基金No.20040005015~~

摘　　要：针对个性化图像检索的语义鸿沟问题,提出了一种新的用户兴趣模型的构建方法。将用户兴趣模型分为长期兴趣和短期兴趣:用户的短期兴趣由图像的低层特征映射得到;用户的长期兴趣经过推理机推理,将短期兴趣映射为高层语义得到,从而弥补语义鸿沟。实验结果表明,经过用户兴趣模型过滤的图像检索结果符合用户的个性化要求,相比已有方法在查准率和查全率上取得了明显的改善。A method for constructing user preference profile in personalized image retrieval is proposed.This method is based on short-term interest and long-term interest,in which the short-tem interest vector is decided by analyzing the image low-lever features,and the long-term interest vector is deduced by collecting interests from inference engine.Experiments results show that the recall/precision are significantly improved and satisfied by personalized user as well.

关 键 词：用户兴趣模型 个性化图像检索 推理机 相关反馈 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]