检索结果-内蒙古大学图书馆

Topological tree for web organisation, discovery and exploration

5th international conference on intelligent data engineering and automated learning, ideal 2004

作者： Freeman, Richard T. Yin, Hujun Department of Electrical and Electronics Engineering University of Manchester Institute of Science and Technology ManchesterM60 1QD United Kingdom

ISBN: (纸本)3540228810

In this paper we focus on the organisation of web contents, which allows efficient browsing, searching and discovery. We propose a method that dynamically creates such a structure called Topological Tree. the tree is generated using an algorithm called automated Topological Tree Organiser, which uses a set of hierarchically organised selforganising growing chains. Each chain fully adapts to a specific topic, where its number of subtopics is determined using entropy-based validation and cluster tendency schemes. the Topological Tree adapts to the natural underlying structure at each level in the hierarchy. the topology in the chains also relates close topics together, thus can be exploited to reduce the time needed for search and navigation. this method can be used to generate a web portal or directory where browsing and user comprehension are improved. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Chains

来源：评论

学校读者我要写书评

暂无评论

Qualified predictions for microarray and proteomics pattern diagnostics with confidence machines

引用

international JOURNAL OF NEURAL SYSTEMS 2005年第4期15卷 247-258页

作者： Bellotti, T Luo, ZY Gammerman, A Van Delft, FW Saha, V Univ London Royal Holloway & Bedford New Coll Comp Learning Res Ctr Egham TW20 0EX Surrey England Canc Res UK Childrens Canc Grp John Vane Sci Ctr London EC1M 6BQ England

We focus on the problem of prediction with confidence and describe a recently developed learning algorithm called transductive confidence machine for making qualified region predictions. Its main advantage, in comparison with other classifiers, is that it is well-calibrated, with number of prediction errors strictly controlled by a given predefined confidence level. We apply the transductive confidence machine to the problems of acute leukaemia and ovarian cancer prediction using microarray and proteomics pattern diagnostics, respectively. We demonstrate that the algorithm performs well, yielding well-calibrated and informative predictions whilst maintaining a high level of accuracy.

关键词： machine learning microarray proteomics classification confidence machine

来源：评论

学校读者我要写书评

暂无评论

An automated on-line traffic flow classification scheme

An automated on-line traffic flow classification scheme

引用

IIH-MSP 2009 - 2009 5th international conference on intelligent Information Hiding and Multimedia Signal Processing

作者： Zhang, Jian Qian, Zongjue Shou, Guochu Hu, Yihong School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China Qingdao University of Technology China

ISBN: (纸本)9780769537627

Traffic classifications based on Statistics methods and Machine learning techniques have attracted a great deal of interest. One challenging issue is that most of supervised algorithms need traffic application information and training data sets to generate classification model offline, which is infeasible to cope with the fast growing number of new applications and online traffic classifications. Cluster algorithms are promising methods. How to identify the feature subset suitable for cluster algorithm is a critical question in our proposed online traffic classification architecture. Two feature selection algorithms Wrapper Search Approach and Correlation-Based Filter Approach are evaluated to find an optimal feature subset. the experiment results demonstrate that Wrapper Search Approach outperforms Correlation-Based Filter Approach in the automated classification architecture. © 2009 IEEE.

关键词： Clustering algorithms

来源：评论

学校读者我要写书评

暂无评论

A novel method for mining frequent subtrees from xml data

引用

5th international conference on intelligent data engineering and automated learning, ideal 2004

作者： Zhang, Wan-Song Liu, Da-Xin Zhang, Jian-Pei Department of Computer Science and Technology Harbin Engineering University Harbin150001 China

ISBN: (纸本)3540228810

In this paper, we focus on the problem of finding frequent subtrees in a large collection of XML data, where both of the patterns and the data are modeled by labeled ordered trees. We present an efficient algorithm RSTMiner that computes all rooted subtrees appearing in a collection of XML data trees with frequent above a user-specified threshold using a special structure Me-tree. In this algorithm, Me-tree is used as a merging tree to supply scheme information for efficient pruning and mining frequent sub-trees. the keys of the algorithm are efficient pruning candidates with Me-Tree structure and incrementally enumerating all rooted sub-trees in canonical form based on a extended right most expansion technique. Experiment results show that RSTMiner algorithm is efficient and scalable. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Trees (mathematics)

来源：评论

学校读者我要写书评

暂无评论

Machine learning in Recent Technology: Shaping the Future of intelligent Applications and data Analysis 5

Machine Learning in Recent Technology: Shaping the Future of...

引用

5th international conference on Sustainable Communication Networks and Application, ICSCNA 2024

作者： Karpagam, P. Uma Maheswari, S. Kumar, A. Pandi, V.Samuthira Jose, P. Virushabadoss, S. Dhanalakshmi College of Engineering Department of Computer Science Engineering India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Biosciences Chennai India Dhanalakshmi College of Engineering Department of Electronics and Communication Engineering Tamil Nadu Chennai India Centre for Advanced Wireless Integrated Technology Chennai Institute of Technology Tamil Nadu Chennai India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of CSE Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798331530013

In the present day, machine learning (ML), which is a subset of artificial intelligence (AI), has emerged as a crucial technology that has revolutionized the way in which we interact with data and construct intelligent applications. the purpose of this study is to investigate the recent developments in machine learning and the profound impact that these breakthroughs have had on a variety of fields, such as the medical field, the financial sector, the transportation industry, and environmental science. through an examination of cutting-edge machine learning techniques such as deep learning, reinforcement learning, and transfer learning, the study sheds light on the ways in which these methodologies are leading to the development of intelligent systems in the future. the purpose of this study is to investigate the function of machine learning in the process of data analysis, with a particular emphasis on its capacity to derive insights from intricate and extensive datasets. Additionally, it studies the difficulties that are linked with machine learning, such as the problem of data privacy, the interpretability of models, and the ethical implications of automated decision-making. the objective of this study is to identify major trends and future directions in machine learning by doing an exhaustive examination of the relevant literature, conducting case studies, and conducting experimental analysis. Based on the findings, it appears that the combination of machine learning with other technologies, such as edge computing and the Internet of things (IoT), will result in intelligent systems that are more advanced and capable of adapting to their environment. the study highlights the significance of a multidisciplinary approach to machine learning, highlighting the necessity of collaboration between computer scientists, domain specialists, and ethicists in order to guarantee the development and deployment of machine learning technologies in a responsible manner. As machin

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Orthogonal least square with boosting for regression

引用

5th international conference on intelligent data engineering and automated learning, ideal 2004

作者： Chen, Sheng Wang, Xunxian Brown, David J. School of Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom Department of Electronic and Computer Engineering University of Portsmouth PortsmouthPO1 3DJ United Kingdom

ISBN: (纸本)3540228810

A novel technique is presented to construct sparse regression models based on the orthogonal least square method with boosting. this technique tunes the mean vector and diagonal covariance matrix of individual regressor by incrementally minimizing the training mean square error. A weighted optimization method is developed based on boosting to append regressors one by one in an orthogonal forward selection procedure. Experimental results obtained using this technique demonstrate that it offers a viable alternative to the existing state-of-art kernel modeling methods for constructing parsimonious regression models. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Mean square error

来源：评论

学校读者我要写书评

暂无评论

A fuzzy set based trust and reputation model in P2P networks

引用

5th international conference on intelligent data engineering and automated learning, ideal 2004

作者： Shuqin, Zhang Dongxin, Lu Yongtian, Yang College of Computer Science and Technology Harbin Engineering University Harbin150001 China Technology Center Chengdu Institute ZTE corporation Chengdu610041 China

ISBN: (纸本)3540228810

Trust plays an important role in making collaborative decisions, so the trust problem in P2P networks has become a focus of research. In this paper, a fuzz set based model is proposed for building trust and reputation in P2P collaborations based on observations and recommendations, and using fuzzy set a peer can present differentiated trust and combine different aspects of trust in collaborations. Depending on fuzzy similarity measure, a good recommenders set can be maintained. the evaluation of the model using simulation experiments shows its effectiveness. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Fuzzy sets

来源：评论

学校读者我要写书评

暂无评论

An automated Railway Unguarded Level Crossing using Lab View 5

An Automated Railway Unguarded Level Crossing using Lab View

引用

5th international conference on IoT Based Control Networks and intelligent Systems, ICICNIS 2024

作者： Mohandass, M.P. Dhanush Nigandan Sri, N. Saron Raj, Y. Stephan, A. KIT-KalaignarKarunanidhi Institute of Technology Department of Electrical and Electronics Engineering Coimbatore India

ISBN: (纸本)9798331518097

this research study introduces an advanced automated system for unguarded railway level crossings, developed using LabView,with the primary objective of enhancing safety and mitigating accident risks. the TDS employs vibration and inductive proximity sensors to reliably detect the approach of trains, providing timely alerts. In parallel, the LCS utilizes a camera module that integrates sophisticated image processing and machine learning algorithms to identify and track vehicles at the crossing accurately. Secure wireless communication between the TDS and LCS is achieved through the AES algorithm, ensuring robust data transmission while minimizing potential vulnerabilities. this automated solution not only delivers real-time alerts for train operators and road users but also enhances the overall efficiency of railway operations. By tackling the significant safety issues posed by unguarded level crossings, the design suggested provides an economical and scalable approach this may greatly enhance public safety and foster sustainable development within the railway infrastructure. © 2024 IEEE.

关键词： Proximity sensors

来源：评论

学校读者我要写书评

暂无评论

Medical Image-to-Image Translation with Spatial Self-Attention for Radiotherapy in Federated learning 5

Medical Image-to-Image Translation with Spatial Self-Attenti...

引用

5th international conference on intelligent data Science Technologies and Applications, IDSTA 2024

作者： Bdair, Tariq Saadeh, Hiba Qaqish, Ban Sulaq, Aya Rawashdeh, Majdi Princess Sumaya University for Technology Data Science Department Amman Jordan Al Yamamah University Software Engineering Department Riyadh Saudi Arabia Princess Sumaya University for Technology Business Information Technology Department Amman Jordan

ISBN: (纸本)9798350354751

Globally, cancer remains a leading cause of death, affecting millions of people each year. Accurate medical imaging is crucial for the effective planning of radiotherapy. However, repeated exposure to radiation from Computed Tomography (CT) scans during treatment planning can put patients at more risk. Fortunately, the recent improvement in automated image-to-image translation using deep learning methods has reached a superior performance. However, this might be challenged by data limitation of requiring a large amount of annotated data assembled in one location, privacy, and motion artifacts in medical imaging. Yet, finding such conditions usually is not feasible. To address this, we propose RadiaSync. RadiaSync is a federated learning framework proposed to train decentralized models in a privacy-preserved fashion. In our method, we use CycleGAN architecture for image translation within an FL environment, ensuring patient privacy and collaborative learning across different clients. Further, we propose a spatial attention mechanism that enhances the translated image quality with more than 55% improvement over the baseline. © 2024 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Fast Frequent Pattern Detection Using Prime Numbers

引用

15th international conference on intelligent data engineering and automated learning (ideal)

作者： Xylogiannopoulos, Konstantinos F. Addam, Omar Karampelas, Panagiotis Alhajj, Reda Univ Calgary Dept Comp Sci Calgary AB T2N 1N4 Canada Hellen Amer Univ Dept Informat Technol Manchester NH USA Global Univ Dept Comp Sci Beirut Lebanon Hellen Air Force Acad Dept Informat Computers Attica Greece

ISBN: (纸本)9783319108407;9783319108391

Finding all frequent itemsets (patterns) in a given database is a challenging process that in general consumes time and space. Time is measured in terms of the number of database scans required to produce all frequent itemsets. Space is consumed by the number of potential frequent itemsets which will end up classified as not frequent. To overcome both limitations, namely space and time, we propose a novel approach for generating all possible frequent itemsets by introducing a new representation of items into groups of four items and within each group, items are assigned one of four prime numbers, namely 2, 3, 5, and 7. the reported results demonstrate the applicability and effectiveness of the proposed approach. Our approach satisfies scalability in terms of number of transactions and number of items.

关键词： frequent pattern mining association rules data mining prime representation

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：