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Clustering by data competition

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Science China(Information Sciences) 2013年第1期56卷 65-77页

作者： lu zhimao ZHANG Qi Pattern Recognition and Natural Computation Laboratory Harbin Engineering University

Clustering analysis is an unsupervised method to find out hidden structures in *** partitional clustering algorithms are sensitive to the selection of initial exemplars,the outliers and *** this paper,a novel technique called data competition algorithm is proposed to solve the *** the concept of aggregation field model is defined to describe the partitional clustering ***,the exemplars are identified according to the data ***,the members will be assigned to the suitable *** competition algorithm is able to avoid poor solutions caused by unlucky initializations,outliers and noise,and can be used to detect the coexpression gene,cluster the image,diagnose the disease,distinguish the variety,*** provided experimental results validate the feasibility and effectiveness of the proposed schemes and show that the proposed approach of data competition algorithm is simple,stable and *** experimental results also show that the proposed approach of data competition clustering outperforms three of the most well known clustering algorithms K-means clustering,affinity propagation clustering,hierarchical clustering.

关键词： data mining clustering analysis partitional clustering data competition

Visual analytics for the clustering capability of data

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Science China(Information Sciences) 2013年第5期56卷 131-144页

作者： lu zhimao LIU Chen ZHANG Qi ZHANG ChunXiang FAN DongMei YANG Peng Pattern Recognition and Natural Computation Laboratory Harbin Engineering University School of Computer Science and Technology Dalian University of Technology School of Software Harbin University of Science and Technology

Clustering analysis is an unsupervised method to find hidden structures in datasets and has been widely used in various ***,it is always difficult for users to understand,evaluate,and explain the clustering results in the spaces with dimension greater than *** high-dimensional visualization of clustering technology can express clustering results well,it still has significant *** this paper,a visualization cluster analysis method based on the minimum distance spectrum(MinDS) is proposed,aimed at reducing the problems of clustering multidimensional ***,the concept of MinDS is defined based on the distance between high-dimensional *** can map any dataset from high-dimensional space to a lower dimension to determine whether the data set is ***,a clustering method which can automatically determine the number of categories is designed based on *** method is not only able to cluster a dataset with clear boundaries,but can also cluster the dataset with fuzzy boundaries through the edge corrosion strategy based on the energy of each data *** addition,strategies for removing noise and identifying outliers are designed to clean datasets according to the characteristics of *** experimental results presented validate the feasibility and effectiveness of the proposed schemes and show that the proposed approach is simple,stable,and efficient,and can achieve multidimensional visualization cluster analysis of complex datasets.

关键词： data mining clustering analysis visual analysis minimum distance spectrum nearest neighbor spectrum outliers

A Complex Encryption System Design Implemented by AES

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Journal of Information Security 2021年第2期12卷 177-187页

作者： zhimao lu Houmed Mohamed Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian China

With the rapid development of internet technology and the increasing popularity of e-commerce, data encryption technology plays a very important role in data security. Information security has two aspects: security protocol and cryptographic algorithm and the latter is the foundation and core technology of information security. Advanced Encryption Standard (AES) encryption algorithm is one of the most commonly used algorithms in symmetric encryption algorithms. Such algorithms face issues when used in the context of key management and security functions. This paper focuses on the systematic analysis of these issues and summarizes AES algorithm implementation, comprehensive application and algorithm comparison with other existing methods. To analyze the performance of the proposed algorithm and to make full use of the advantages of AES encryption algorithm, one needs to reduce round key and improve the key schedule, as well as organically integrate with RSA algorithm. Java language is used to implement the algorithm due to its large library, then to show the efficiency of the proposed method we compare different parameters, such as encryption/decryption speed, entropies and memory consumption...) with a classic algorithm. Based on the results of the comparison between AES and the hybrid AES algorithm, the proposed algorithm shows good performance and high security. It therefore can be used for key management and security functions, particularly for sharing sensitive files through insecure channel. This analysis provides a reference useful for selecting different encryption algorithms according to different business needs.

关键词： AES Algorithm RSA Algorithm Encryption Key Management

Extracting Knowledge from On-Line Forums for Non-Obstructive Psychological Counseling Q&A System

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International Journal of Intelligence Science 2012年第2期2卷 40-48页

作者： Yuanchao Liu Ming Liu zhimao lu Mingkai Song Information and Communication Engineering College Harbin Engineering University Harbin China School of Computer Science and Technology Harbin Institute of Technology Harbin China

Psychological counseling Q&A system is enjoying a remarkable and increasing popularity in recent years. Knowledge base is the important component for such kind of systems, but it is difficult and time-consuming to construct the knowledge base manually. Fortunately, there emerges large number of Q&A pairs in many psychological counseling websites, which can provide good source enriching the knowledge base. This paper presents the method of knowledge extraction from psychological consulting Q&A pairs of on-line psychological counseling websites, which include keywords, semantic extension and word sequence. P-XML, which is the knowledge template based on XML, is also designed to store the knowledge. The extracted knowledge has been successfully used in our non-obstructive psychologycal counseling system, called P.A.L., and the experimental results also demonstrated the feasibility and effectiveness of our approach.

关键词： Knowledge Base Construction Keyword Extraction Q&A System Chatterbot

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近邻传播的文本聚类集成谱算法

哈尔滨工程大学学报 2012年第7期33卷 899-905页

作者：卢志茂李纯张琦哈尔滨工程大学信息与通信工程学院中国人民解放军91685部队

针对现有聚类集成谱算法聚类结果不稳定的问题,引入近邻传播聚类思想,设计了基于近邻传播的聚类集成谱算法(APCESA).该算法先由聚类集成和谱分得到空间结构相对简单的文本低维嵌入,然后通过近邻传播算法得到最终的聚类结果.在谱分解过程... 详细信息

针对现有聚类集成谱算法聚类结果不稳定的问题,引入近邻传播聚类思想,设计了基于近邻传播的聚类集成谱算法(APCESA).该算法先由聚类集成和谱分得到空间结构相对简单的文本低维嵌入,然后通过近邻传播算法得到最终的聚类结果.在谱分解过程中,采用矩阵变换方法,避免了谱算法中特征值分解的高昂计算代价.对真实文本数据集的实验结果表明,所提算法比对比算法聚类更稳定,且聚类结果的NMI值和ANMI值均高于对比算法.

关键词：近邻传播聚类集成文本聚类谱聚类矩阵变换

WORD SENSE DISAMBIGUATION BASED ON IMPROVED BAYESIAN CLASSIFIERS

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Journal of Electronics(China) 2006年第3期23卷 394-398页

作者： Liu Ting lu zhimao Li Sheng Computer Science ＆ Technology School Harbin Institute of Technology Harbin 150001 China Computer Science ＆ Technology School Harbin Engineering University Harbin 150001 China

Word Sense Disambiguation (WSD) is to decide the sense of an ambiguous word on particular context. Most of current studies on WSD only use several ambiguous words as test samples, thus leads to some limitation in practical application. In this paper, we perform WSD study based on large scale real-world corpus using two unsupervised learning algorithms based on ±n-improved Bayesian model and Dependency Grammar (DG)-improved Bayesian model. ±n-improved classifiers reduce the window size of context of ambiguous words with close-distance feature extraction method, and decrease the jamming of useless features, thus obviously improve the accuracy, reaching 83.18% (in open test). DG-improved classifier can more effectively conquer the noise effect existing in Naive-Bayesian classifier. Experimental results show that this approach does better on Chinese WSD, and the open test achieved an accuracy of 86.27%.

关键词： Word Sense Disambiguation (WSD) Natural Language Processing (NLP) Unsupervised learning algorithm Dependency Grammar (DG) Bayesian classifier

HawkEyes Plagiarism Detection System

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国际计算机前沿大会会议论文集 2015年第1期 134-135页

作者： Leilei Kong Jie Li Feng Zhao Haoliang Qi Zhongyuan Han Yong Han zhimao lu School of Computer Science and Technology Heilongjiang Institute of TechnologyHarbinChina College of Information and Communication Engineering Harbin Engineering UniversityHarbinChina School of Computer Science and Technology Harbin Institute of TechnologyHarbinChina

The high-obfuscation plagiarism detection in big data environment,such as the paraphrasing and cross-language plagiarism, is often difficult for anti-plagiarism system because the plagiarism skills are becoming more and more complex. This paper proposes HawkEyes, a plagiarism detection system implemented based on the source retrieval and text alignment algorithms which developed for the international competition on plagiarism detection organized by CLEF. The text alignment algorism in HawkEyes gained the first place in PAN@CLEF2012. In the demonstration, we will present our system implemented on PAN@CLEF2014 training data corpus.

关键词： plagiarism detection system source retrieval text alignment

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基于特征帧构建的运动目标检测方法

红外与激光工程 2012年第7期41卷 1959-1963页

作者：卢志茂刘明华刘晨哈尔滨工程大学信息与通信工程学院黑龙江哈尔滨150001

非参数密度估计在样本分析建模方面得到了很大的关注,尤其是核密度估计方法。但由于核密度估计方法计算量大,应用到运动目标检测方面很难达到实时效果。提出了一种特征帧构建的核密度估计方法。因为核密度估计不需要假设背景模型的密度... 详细信息

非参数密度估计在样本分析建模方面得到了很大的关注,尤其是核密度估计方法。但由于核密度估计方法计算量大,应用到运动目标检测方面很难达到实时效果。提出了一种特征帧构建的核密度估计方法。因为核密度估计不需要假设背景模型的密度分布函数,所有样本值又满足独立同分布的原则,所以可以通过特征帧构建的方法进行背景建模,同时应用此方法进行背景更新。实验结果表明:该方法能够适应环境变化且具有运算速度快、实时性好等特点,可以将其应用到复杂背景下的监控系统中。

关键词：核密度估计运动目标检测背景建模特征帧

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基于主动学习的短语翻译对获取

高技术通讯 2011年第4期21卷 380-385页

作者：张春祥赵铁军卢志茂哈尔滨理工大学软件学院哈尔滨150080 哈尔滨工业大学计算机科学与技术学院语言语音教育部-微软重点实验室哈尔滨150001 哈尔滨工程大学信息与通信工程学院哈尔滨150001

利用汉-英双语句对进行了抽取短语翻译对的研究，提出了一种利用双语评价特征进行译文评价的短语翻译对主动获取方法。该方法通过选择有代表性的短语翻译对来达到减少人工标注数据的目的，以短语译文直译率、短语翻译概率和短语长度差... 详细信息

利用汉-英双语句对进行了抽取短语翻译对的研究，提出了一种利用双语评价特征进行译文评价的短语翻译对主动获取方法。该方法通过选择有代表性的短语翻译对来达到减少人工标注数据的目的，以短语译文直译率、短语翻译概率和短语长度差异为基础，使用标注后的短语翻译对对支持向量机（SVM）进行训练，并使用优化后的SVM对测试数据进行分类。实验结果表明，使用此方法，在分类器性能基本没有下降的前提下，人工标注数据量减少了80％。

关键词：短语翻译对双语句对双语评价特征主动获取支持向量机(SVM)