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检索条件"任意字段=4th International Conference on Machine Learning and Data Minining in Pattern Recognition"

共 1786 条记录，以下是1401-1410 订阅

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the application research of Extenics in association rules data mining

The application research of Extenics in association rules da...

引用

4th international conference on machine Vision (ICMV) - Computer Vision and Image Analysis - pattern recognition and Basic Technologies

作者： Li, Qingshui Jiang, Wenhua Zhejiang Univ Technol Hangzhou Zhejiang Peoples R China Hangzhou Engn Construct Qual & Safety Supervise A Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9780819490261

this article describes the theory knowledge of the extenics and association rules, And combined extension and association rule mining algorithm, Construction of a database element model, the complex database reduced to intuitive and simple database, make expression more clear, and reduce the next step rule mining of data calculation. In the basic of Apriori algorithm significant association rules data mining based on the extension. Using association rule mining algorithm and extension of the correlation thought the database of extension of data mining association rules, access to many valuable association rules. And an example illustrates the effectiveness of this method.

关键词： Extenics association rules apriori algorithm extension association rules

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Research on transformation and optimization of large scale 3D modeling for realtime rendering

Research on transformation and optimization of large scale 3...

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4th international conference on machine Vision (ICMV) - Computer Vision and Image Analysis - pattern recognition and Basic Technologies

作者： Hu, Yan Yang, Yongchao Zhao, Gang He, Bin Shen, Guosheng Huazhong Normal Univ Natl Engn Res Ctr E Learning Wuhan 430079 Hubei Peoples R China

ISBN: (纸本)9780819490261

During the simulation process of real-time three-dimensional scene, the popular modeling software and the real-time rendering platform are not compatible. the common solution is to create three-dimensional scene model by using modeling software and then transform the format supported by rendering platform. this paper takes digital campus scene simulation as an example, analyzes and solves the problems of surface loss;texture distortion and loss;model flicker and so on during the transformation from 3Ds Max to MultiGen Creator. Besides, it proposes the optimization strategy of model which is transformed. the operation results show that this strategy is a good solution to all kinds of problems existing in transformation and it can speed up the rendering speed of the model.

关键词： Model Transformation Large-scale three-Dimensional Scene model Model Optimization data loss Realtime rendering

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A Framework of Chinese Semantic Text Mining Based on Ontology learning

A Framework of Chinese Semantic Text Mining Based on Ontolog...

引用

4th international conference on machine Vision (ICMV) - machine Vision, Image Processing and pattern Analysis

作者： Zhang, Yu-feng Hu, Feng Wuhan Univ Ctr Studies Informat Resources Wuhan Peoples R China Guangdong Univ Technol Sch Management Guangzhou Peoples R China

ISBN: (纸本)9780819490254

Text mining and ontology learning can be effectively employed to acquire the Chinese semantic information. this paper explores a framework of semantic text mining based on ontology learning to find the potential semantic knowledge from the immensity text information on the Internet. this framework consists of four parts: data Acquisition, Feature Extraction, Ontology Construction, and Text Knowledge pattern Discovery. then the framework is applied into an actual case to try to find out the valuable information, and even to assist the consumers with selecting proper products. the results show that this framework is reasonable and effective.

关键词： Text mining semantic mining ontology learning

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A Novel Approach to Improve the Scalability of the Relational Model

A Novel Approach to Improve the Scalability of the Relationa...

引用

4th international conference on machine Vision (ICMV) - Computer Vision and Image Analysis - pattern recognition and Basic Technologies

作者： Zhang, Jianying Wang, Xiukun Yu, Hong Dalian Univ Technol Sch Comp Dalian Peoples R China Dalian Fisheries Univ Dept Comp Sci Dalian Peoples R China

ISBN: (纸本)9780819490261

Nowadays, the relation model faces the challenge of being applied to massively distributed databases and cloud databases. It can not be easily scaled out in such computing environments. the main reason is lack of a proper data distribution unit and a uniform data distribution model. In this paper, a new data distribution model is proposed. As semantic clusters of data, data multitrees are taken as the distribution units. Schema multitree and data multitree are defined, and then a method of designing the schema graph is proposed to ensure that the data graph is a data multitree. three theorems proved the correctness of the proposed method. Since relational databases can be viewed as data multitrees, the sematic related data can be split or unified together easily with multiree operations, the scalability of relational model can be improved. In addition, this data distribution model is transparent to programmers.

关键词： relational model multitree data distribution multi-hierarchical model cloud DB

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Efficient storage management for distributed storage system

Efficient storage management for distributed storage system

引用

4th international conference on machine Vision (ICMV) - Computer Vision and Image Analysis - pattern recognition and Basic Technologies

作者： Phyu, Myat Pwint thein, Ni Lar Univ Comp Studies Yangon Myanmar

ISBN: (纸本)9780819490261

As storage systems grow larger and more complex, the traditional block-based file systems cannot satisfy the large workload. More recent distributed file systems have adopted architectures based on object-based storage. this paper presents a framework of efficient storage management for distributed storage system. In object storage side, low-level storage tasks and data distribution must be managed and in metadata server side, we will manage how to scale the metadata. Due to the high space efficiency and fast query response, bloom filters have been widely utilized in recent storage systems. So, we will also utilize bloom-filter based approach to manage metadata by taking the advantages of bloom-filter and the semantic-based scheme will also be used to narrow the managed workload. In this paper, we will neglect the data distribution of object-based storage side.

关键词： Object-based storage metadata management bloom-filter unstructured data

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AN OBJECT ORIENTED MULTIDIMENSIONAL MODEL FOR data WAREHOUSE

AN OBJECT ORIENTED MULTIDIMENSIONAL MODEL FOR DATA WAREHOUSE

引用

4th international conference on machine Vision (ICMV) - Computer Vision and Image Analysis - pattern recognition and Basic Technologies

作者： Gosain, Anjana Mann, Suman Guru Gobind Singh Indraprastha Univ USIT Delhi India Maharaja Surajmal Inst Technol Delhi India Guru Gobind Singh Indraprastha Univ USIT Delhi India

ISBN: (纸本)9780819490261

Organizations, to have a competitive edge upon each other, resort to business intelligence which refers to information available for enterprise to make strategic decisions. data warehouse being the repository of data provides the backend for achieving business intelligence. the design of data warehouse, thereby, forms the key, to extract and obtain the relevant information facilitating to make strategic decisions. the initial focus for the design had been upon the conceptual models but now object oriented multidimensional modelling has emerged as the foundation for the designing of data warehouse. Several proposals have been put forth for object oriented multidimensional modelling, each incorporating some or other features, but not all. this paper consolidates all the features previously introduced and the new introduced, thus, proposing a new model having features to be incorporated while designing the data warehouse.

关键词： data Warehouse Multidimensional Model Object Oriented Model Unified Modelling Language Online analytical processing

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Classification of sole patterns from a 3-Dimensional shoe model

Classification of sole patterns from a 3-Dimensional shoe mo...

引用

4th international conference on machine Vision (ICMV) - Computer Vision and Image Analysis - pattern recognition and Basic Technologies

作者： Zhao, Qingmin Dong, Feifei Wu, Jianhua Cheng, Jian Zhu, Yican Nanchang Univ Elect & Informat Engn Dept Nanchang Jiangxi Peoples R China Jiangxi Prov Publ Secur Bur Ctr Forens Inst Nanchang Jiangxi Peoples R China

ISBN: (纸本)9780819490261

the purpose of this paper is to classify the sole patterns from a 3D shoe model which is comprised of scattered point cloud data. Sole patterns can be divided into five categories based on the texture of each pattern. the point cloud data is sliced into a number of layers, and the unordered data points in each layer are projected onto a viewing plane to get a 2D shoeprint, in which we can further segment a texture element by region growing. then, each texture element segmented can be classified into two types, non-closed curve and closed curve, by detecting if there are point cloud data in each external unit of the region and looking for the nearest points to the region. Finally, we can identify the type of the texture element into one of the five categories by analyzing its geometrical characteristics.

关键词： sole pattern point cloud data closed curve region growing classification

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Cumulative restricted boltzmann machines for ordinal matrix data analysis

Cumulative restricted boltzmann machines for ordinal matrix ...

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4th Asian conference on machine learning, ACML 2012

作者： Tran, Truyen Phung, Dinh Venkatesh, Svetha Pattern Recognition and Data Analytics Deakin University Waurn Ponds VIC 3216 Australia Department of Computing Curtin University Bentley WA 6102 Australia

Ordinal data is omnipresent in almost all multiuser-generated feedback - questionnaires, preferences etc. this paper investigates modelling of ordinal data with Gaussian restricted Boltzmann machines (RBMs). In particular, we present the model architecture, learning and inference procedures for both vector-variate and matrix-variate ordinal data. We show that our model is able to capture latent opinion profile of citizens around the world, and is competitive against state-of-art collaborative filtering techniques on large-scale public datasets. the model thus has the potential to extend application of RBMs to diverse domains such as recommendation systems, product reviews and expert assessments. © 2012 T. Tran, D. Phung & S. Venkatesh.

关键词： Matrix algebra

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Class-Specific Mahalanobis Distance Metric learning for Biological Image Classification

Class-Specific Mahalanobis Distance Metric Learning for Biol...

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9th international conference on Image Analysis and recognition (ICIAR)

作者： Mohan, B. S. Shajee Sekhar, C. Chandra Computer Science and Engineering Department Indian Institute of Technology Madras Chennai 600036 India

ISBN: (纸本)9783642312984

Distance metric learning (DML) is an emerging field of machine learning. the basic idea behind DML is to adapt the underlying distance metric to improve the performance for the pattern analysis tasks. In this paper, we present the use of DML techniques to improve the classification accuracy of kappa-Nearest Neighbour classifier (kappa NN) used for biological image classification tasks. the distance metric learning technique is used for learning the Mahalanobis distance metric. the learning problem is cast into a Bregman optimization problem that minimizes the LogDet divergence subject to linear constraints. We propose the class-specific Mahalanobis distance metric learning for further improvement of the performance of the kappa NN classifier. Results of our studies on benchmark data sets demonstrate the effectiveness of the distance metric learning techniques in classification of biological images.

关键词： Distance metric learning kappa NN classifier Class specific Mahalanobis distancemetric learning Bregman divergence LogDet divergence

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data with Shifting Concept Classification Using Simulated Recurrence

Data with Shifting Concept Classification Using Simulated Re...

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4th international Scientific Asian conference on Intelligent Information and database Systems (ACIIDS)

作者： Sobolewski, Piotr Wozniak, Michal Wroclaw Univ Technol Dept Syst & Comp Networks Fac Elect PL-50370 Wroclaw Poland

ISBN: (纸本)9783642284878

One of the serious problems of modern pattern recognition is concept drift i.e., model changing during exploitation of a given classifier. the paper proposes how to adapt a single classifier system to the new model without the knowledge of correct classes. the proposed simulated concept recurrence is implemented in the non-recurring concept shift scenario without the drift detection mechanism. We assume that the model could change slightly, what allows us to predict a set of possible models. Quality of the proposed algorithm was estimated on the basis of computer experiment which was carried out on the benchmark dataset.

关键词： Concept shift classifier ensemble simulated recurrence machine learning

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