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auto relevance feedback 自动相关反馈
In this dissertation, a relevance feedback method using feature subspaces analysis (FSA) is proposed for content-based image retrieval. 论文提出了基于特征子空间分析的相关反馈方法。
Finally, the precisions and recalls of single feature, multi-feature integration and relevance feedback are calculated and compared. 最后分别给出基于单一特征，特征融合和相关反馈方法的查准率和查全率，并对试验结果进行分析。
Salton, G. &Buckley, C. "Improving retrieval performance by relevance feedback," Journal of The American Society for Information Science, 41(4), 1990, pp.288-297. 李宜容，"人文及社会学科读者使用线上公用目录检索词汇之研究"，淡江大学教育资料科学研究所硕士论文，民85年。
Thirdly, an emphasized research is focused on the appliance of relevance feedback in CBIR, and an improved method based on the relevance of the users is given. 本文重点研究了相关反馈机制在图像检索中的应用，给出了一种基于用户反馈的交互式图像检索方法。
This paper puts forward one technique for Relevance Feedback Based on Conceptual Graphs.We can make decision that two concepts are similarity from their semantic. 文章提出了一种基于概念图的相关反馈技术,采用概念图的知识表示方式描述概念之间关系,从语义的层次上进行相似度判断,扩展查询式。
CBIR (Content-based Image Retrieval),Relevance Feedback,Model of Image Retrieval,Vision Feature,Bayesian Classifier,Sematic NetWork,Query Interface,Retrieval Engine. 01基于内容图像检索,相关反馈,图像检索模型,视觉特征,贝叶斯分类器,语义网络,查询接口,检索引擎
In addition, relevance feedback techology in CBIR system has also been researched, we develop a model of relevance feedback and design a system framework. 此外,本文还研究了相关反馈技术在图像检索系统中的应用,实现了一种基于相关反馈的交互式图像检索模型,并设计了系统框架。
The spatial and temporal characteristics of relevance feedback information in content-based image retrieval are analyzed, based on which a novel relevance feedback learning method, namely, TSC-SVM is proposed. 本文深入研究了相关反馈的人机交互方法，分析了基于内容的图像检索中相关反馈信息的时间特性与空间特性，在此基础上首次提出了一种时空约束支持向量机(TSC-SVM)的相关反馈学习方法。
RL acquires the best path by keeping feed back to the environment，which is consistent the idea of relevance feedback acquires the best answer by grouping the retrieval intention of users. 由于强化学习是通过不断对环境的反馈来获得最佳的路径，这与相关反馈通过对用户检索意图的摸索来获得最优答案的思想一致。
RUI Y,HUANG T,MEHROTRA S.A relevance feedback architecture for content-based multimedia information systems.Workshop on Content Based Access of Image and Video Libraries,Porto Rico,June 1997. 方艳梅等.;基于内容图像检索系统的性能改进方法
Finally gives the relevance feedback algorithm of based NMI and entropy feature according to the trademark library.Experimental results show that it can improve retrieval accuracy. 最后结合商标图象库给出了基于NMI和信息熵的相关反馈算法，实验结果表明，可进一步提高检索精度。
The Detroit auto workers went out for higher pay. 底特律的汽车工人为争取提高工资而罢工。
He made the best time in the auto race. 他的汽车赛中开得最快。
These similarities and historical relevance feedbacks deposited in the neural network can be used in next retrievals to gain enhancement in the efficiency of the system retrieval. 图像间的这种相似性以及本次检索结果可以作为以后检索的历史信息保存在神经网络中，从而提高下一次检索的效率。
In that period auto sales hit a14-year low. 这时期汽车销售量达到14年来最低水平。
Another auto store was opened in town yesterday. 昨天镇上又开了一家汽车商行。
He was maimed in an auto accident. 他在一次车祸中成了残废。
Similarity Measurement and Relevance Feedback in Image Retrieval 图像内容检索中的相似性度量和相关反馈
With the technology of Multi-Agent Cooperation,Meta-Search,machine learning based on relevant feedback,and improved algorithm with PageRank for Agent crawl,the system implements efficient,personalized and initiative online information retrieval. 该系统采用多Agent协作技术 ,Meta -Search技术 ,相关反馈学习算法 ,以及结合PageRank的期望度启发爬行算法 ,实现了高效的个性化 ,主动式在线信息发现。