[1]孙正兴,张尧烨,李? 彬.基于线性规划分类器的相关反馈技术[J].智能系统学报,2007,2(3):34-38.
SUN Zheng-xing,ZHANG Yao-ye,LI Bin.Applying relevance feedback with a linear programming classifier[J].CAAI Transactions on Intelligent Systems,2007,2(3):34-38.
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SUN Zheng-xing,ZHANG Yao-ye,LI Bin.Applying relevance feedback with a linear programming classifier[J].CAAI Transactions on Intelligent Systems,2007,2(3):34-38.
基于线性规划分类器的相关反馈技术
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
2
期数:
2007年第3期
页码:
34-38
栏目:
学术论文—机器学习
出版日期:
2007-06-25
- Title:
- Applying relevance feedback with a linear programming classifier
- 文章编号:
- 1673-4785(2007)03-0034-05
- 分类号:
- TP391;TP126
- 文献标志码:
- A
- 摘要:
- 提出了一种基于线性规划分类器的相关反馈方法.所设计的线性规划分类器将特征选择和分类学习结合起来，使其不仅能在利用用户标注的小样本条件下进行实时训练，而且能根据样本对分类的贡献程度选择用户反馈中的敏感特征，从而能在相关反馈小样本训练条件下有效捕捉用户的反馈意图.针对草图检索的实验结果验证了所提出方法在相关反馈中的有效性.
- Abstract:
- This paper presents a method of applying relevance feedback to an auto mated sketch retrieval system by means of linear programming (LP) classification . A linear programming classifier was designed by combining feature selection wi th classification learning. The proposed classifier not only achieved real-time learning based on small sets of user-annotated samples, but also identified sens itive features from user’s interactive selections according to their contributi on to the classification of candidate sketches, effectively capturing the intent of user feedback with only a small set of training samples giving relevance fee dback. Experiments in sketch retrieval prove that the proposed method is both ef fective and efficient for relevance feedback.
- 参考文献/References:
-
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［3］MACARTHUS S D, BRODLEY C E, SHYU C. Relevance feedback decision trees in c on tentbased image retrieval ［A］. Proceedings of IEEE Workshop on ContentBase d Access to Image and Video Libraries［C］.South Carolina, 2000.
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［7］CHU H H, CHI H C, HUANG K Z, et al. Biased support vector machine for rele va nce feedback in image retrieval ［A］. Proceedings of International Joint Confer ence on Neural Networks［C］.Budapest, Hungary, 2004
［8］JAIN A, ZONGKER D. Feature selection: evaluation, application, and small s am ple performance ［J］. IEEE Transactions on Pattern Analysis and Machine Intelli gence, 1997,2(19):153-158.
［9］MANGASARIAN O L. Linear and nonlinear separation of patterns by linear pro gramming ［J］. Operations Research, 1965, 9(5)： 444-452.
［10］BENNETT K P, MANGASARIAN O L. Robust linear programming discrimin ation of t ow linearly inseparable sets ［J］. Optimization Method and Software, 1992, 1(1) : 23-34.
［11］BRADLEY P S, MANGASARIAN O L. Feature selection via concave minimization an d support vector machines ［A］.Proceeding of 5th International Conference on M achine Learning［C］.［s.l.］,1998.
［12］GUO G, DYER C R. Learning from examples in the small sample case: face ex pression recognition ［J］. IEEE Transactions on Systems Man and Cybernetics, 2 005, 35(3): 477-488.
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备注/Memo
收稿日期：2006-10-31.
基金项目：国家自然科学基金资助项目（69903006，60373065 ）.
作者简介：孙正兴，男，1964年生，博士，教授、博士生导师.主要研究方向为多媒体计算、计算机视觉和智能人机交互，先后获省部级科技进步三等奖3次.已在国内外重要学术刊物上发表学术论文80余篇，出版专著2部. E-mail:szx@nju.edu.cn；张尧烨，男，1983年生，硕士研究生，主要研究方向为信息检索与智能人机交互；李 彬，男，1982年生，硕士研究生，主要研究方向为信息检索与智能人机交互.
更新日期/Last Update:
2009-05-07