检索结果-内蒙古大学图书馆

11th IEEE international conference on data Mining, ICDM 2011

作者： Hu, Po Huang, Minlie Xu, Peng Li, Weichang Usadi, Adam K. Zhu, Xiaoyan Department of Computer Science and Technology State Key Laboratory on Intelligent Technology and Systems Tsinghua University Beijing China ExxonMobil Research and Engineering Company NJ United States

ISBN: (纸本)9780769544083

though news readers can easily access a large number of news articles from the Internet, they can be overwhelmed by the quantity of information available, making it hard to get a concise, global picture of a news topic. In this paper we propose a novel method to address this problem. Given a set of articles for a given news topic, the proposed method models theme variation through time and identifies the breakpoints, which are time points when decisive changes occur. For each breakpoint, a brief summary is automatically constructed based on articles associated with the particular time point. Summaries are then ordered chronologically to form a timeline overview of the news topic. In this fashion, readers can easily track various news topics efficiently. We have conducted experiments on 15 popular topics in 2010. Empirical experiments show the effectiveness of our approach and its advantages over other approaches. © 2011 IEEE.

关键词： data mining

来源：评论

学校读者我要写书评

暂无评论

Tweetsemminer: A meta-topic identification model for twitter using semantic analysis

引用

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8669卷 69-76页

作者： Menéndez, Héctor D. Delgado-Calle, Carlos Camacho, David Departamento de Ingeniería Informática Escuela Politécnica Superior Universidad Autónoma de Madrid C/Francisco Tomás y Valiente 11 Madrid28049 Spain

ISBN: (纸本)9783319108391

the information contained in Social Networks has become increasingly important over the last few years. Inside this field, Twitter is one of the main current information sources, produced by the comments and contents that their users interchange. this information is usually noisy, however, there are some hidden patterns that can be extracted such as trends, opinions, sentiments, etc. these patterns are useful to generate users communities, which can be focused, for example, on marketing campaigns. Nevertheless, the identification process is usually blind, difficulting this information extaction. Based on this idea, this work pretends to extract relevant data from Twitter. In order to achieve this goal, we have desgined a system, called TweetSemMiner, to classify user comments (or tweets) using general topics (or meta-topics). there are several works devoted to analize social networks, however, only Topic Detection techniques have been applied in this context. this paper provides a new approach to the problem of classification using semantic analysis. the system has been developed focused on the detection of a single meta-topic and uses techniques such as Latent Semantic Analysis (LSA) combined with semantic queries in DBpedia, in order to obtain some results which can be used to analyze the effectiveness of the model. We have tested the model using real users, whose comments were subsequently evaluated to check the effectiveness of this approach. © Springer international Publishing Switzerland 2014.

关键词： Marketing

来源：评论

学校读者我要写书评

暂无评论

11th EAI international conference on MOBILe Wireless MiddleWARE, Operating Systems and Applications, MOBILWARE 2022

11th EAI International Conference on MOBILe Wireless MiddleW...

引用

11th EAI international conference on MOBILe Wireless MiddleWARE, Operating Systems and Applications, MOBILWARE 2022

ISBN: (纸本)9783031344961

the proceedings contain 23 papers. the special focus in this conference is on MOBILe Wireless MiddleWARE, Operating Systems and Applications. the topics include: Design of Aerospace Cloud Computing Server Based on Docker Cluster;analysis and Simulation of High Orbit Weak Signal Tracking Algorithm;avionics System Architectures for Software-Defined Spacecraft;research and Application of Energy Efficiency Optimization Algorithm for Spacecraft Simulation Platform;SADA: SDN Architecture Based Secure Dynamic Access Scheme for Satellite Network;Research on the Concept and Connotation of Space Proving Grounds (SPG);a Multi-agent Based Satellite Health Management System Architecture and Implementation Scheme;avionic System Architecture Design of the Manned Deep Space Exploration Spacecraft;research on Tianwen-1 Mars Probe Relay Communication Technology;Deep Reinforcement learning Based Congestion Control Mechanism for SDN and NDN in Satellite Networks;Design and Practice of Communication System During EDL for Mars Probe;Study on EMC Influence of Zhu Rong Rover UHF Band Communication System;design and Implementation of Power Supply and Distribution System for Mars Landing Mission;research on Integrated Operation Design of Low Orbit Remote Sensing Satellite for intelligent Application;intelligent automated Penetration Testing Using Reinforcement learning to Improve the Efficiency and Effectiveness of Penetration Testing;time Slot Correlation-Based Caching Strategy for Information-Centric Satellite Networks;design and Implementation of a Pipeline-Based data Scheduling Method for Spacecraft with Multiple data Buses;Research on the Development of intelligent Space System (ISS);features Extraction of Reconstruction Model Using in Augmented Reality System of Teleoperation Mobile Robots;research on Rapid 3D Reconstruction for Teleoperation in Manned Lunar Exploration Mission.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Static packet routing in NoC platform using ACO-based algorithms

Static packet routing in NoC platform using ACO-based algori...

引用

13th international conference on intelligent data engineering and automated learning, ideal 2012

作者： Silva Jr., Luneque Nedjah, Nadia De Macedo Mourelle, Luiza Systems Engineering and Computer Science Program COPPE Federal University of Rio de Janeiro Brazil Department of Electronics Engineering and Telecommunications State University of Rio de Janeiro Brazil Department of Systems Engineering and Computation State University of Rio de Janeiro Brazil

ISBN: (纸本)9783642326387

Networks-on-Chip (NoC) have been used as an interesting option in design of communication infrastructures for embedded systems, providing a scalable structure and balancing the communication between cores. Because several data packets can be transmitted simultaneously through the network, an efficient routing strategy must be used in order to avoid congestion delays. In this paper, ant colony algorithms were used to find and optimize routes in a mesh-based NoC, where several randomly generated applications have been mapped. the routing optimization is driven by the minimization of total latency in packets transmission between tasks. the simulation results show the effectiveness of the ant colony inspired routing by comparing it with general purpose algorithms for deadlock free routing. © 2012 Springer-Verlag.

关键词： Ant colony optimization

来源：评论

学校读者我要写书评

暂无评论

Usability requirements for COTS based systems 09

Usability requirements for COTS based systems

引用

11th international conference on Information Integration and Web-based Applications and Services, iiWAS2009

作者： Alsumait, Asmaa Habib, Sami Kuwait University Computer Engineering Department P. O. Box 5969 Safat 13060 Kuwait

ISBN: (纸本)9781605586601

Component-based software development (CBSD) aims at building software systems by searching, selecting and integrating commercial off-the-shelf (COTS) components. the effective selection of COTS components that meet the user's requirements and expectations is a non-trivial task. Many published papers consider functional requirements while ignoring usability requirements. In this paper, we have proposed a selection process approach (SPA), which allows an effective selection of the COTS components while minimizing the cost and assuring the satisfaction of hardware, software and user usability requirements. SPA includes requirement solver (RS), an automated tool to assess requirement engineers to select components that creates a functioning computer system. RS optimizes the solution using Simulated Annealing (SA) to search the design space to match, rank, select and integrate COTS components with a maximal satisfaction while neither exceeding a given budget nor violating user and performance constraints. Our computational results based on building a computer for a child handwriting e-learning application show feasibility of SPA in finding solution satisfying all constraints while reducing the cost by 58%. © 2010 ACM.

关键词： Simulated annealing

来源：评论

学校读者我要写书评

暂无评论

BP neural networks combined with PLS applied to pattern recognition of Vis/NIRs

引用

7th international conference on intelligent data engineering and automated learning, ideal 2006

作者： Di, Wu Yong, He Yongni, Shao Shuijuan, Feng College of Biosystems Engineering and Food Science Zhejiang University 310029 Hangzhou China

ISBN: (纸本)3540454853

Vis/NIRs technique can be used in non-destructive measurement of the material internal quality in many fields. In this study, a mixed algorithm combined with back-propagation neural networks (BPNNs) and partial least squares (PLS) method was applied in the predicting the acidity of yogurt. the reflectance of optimal wavebands selected by PLS process were set as input neurons of BPNNs to establish the prediction model. By training the 130 yogurt samples in the BPNNs of topological structure 19:11:1, the acidity of the remaining 25 samples were predicted. the correlation between the measured and predicted values shows an excellent prediction performance with the value of 0.97, higher than the result (0.916) obtained only by PLS. thus, it is concluded that the algorithm construct by BPNNs combined with partial least square applied to pattern recognition is an available alternative for pattern recognition based on Vis/NIRs. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Nondestructive examination

来源：评论

学校读者我要写书评

暂无评论

A Review Paper on Designing intelligent Intrusion Detection System Using Deep learning 11

A Review Paper on Designing Intelligent Intrusion Detection ...

引用

11th international conference on Emerging Trends in engineering and Technology - Signal and Information Processing, ICETET - SIP 2023

作者： Wasnik, Priyanka Chavhan, Nekita G H Raisoni College of Engineering Department of Computer Science and Engineering Nagpur India G H Raisoni College of Engineering IoT and Cyber Security Department of Data Science Nagpur India

ISBN: (纸本)9798350348422

Machine learning techniques have been have proven to be more effective than conventional extensively used in the creation of intrusion detection systems (IDS) that can swiftly and automatically identify and classify cyber attacks at the host-and network-levels. A scalable solution is needed since destructive attacks are happening so quickly and are changing all the time. For more investigation, the malware community has access to a number of malware databases. the performance of several machine learning algorithms on a range of datasets that were made available to the general public, however, has not yet been thoroughly evaluated by any study. the publicly available malware datasets should be regularly updated and benchmarked due to the dynamic nature of malware and the continuously evolving attacking techniques. In this study, a deep neural network (DNN), a type of deep learning model, is examined in order to create a flexible and efficient IDS to identify and categorise unexpected and unanticipated cyber threats. In order to analyse a variety of datasets that have been produced throughout time using both static and dynamic methodologies, it is vital to take into account the rapid increase in attacks and the constant evolution of network behaviour. It is simpler to select the most effective algorithm for accurately predicting forthcoming cyber attacks with the help of this type of research. Many publicly available benchmark malware datasets are used to offer a thorough review of DNN and other conventional machine learning classifier studies. the KDDCup 99 dataset and the accompanying hyper parameter selection techniques are used to choose the ideal network parameters and topologies for DNNs. A learning rate of [0.01-0.5] is applied to every 1,000-epoch DNN experiment. A variety of datasets, including NSL-KDD, UNSW-NB15, Kyoto, WSN-DS, and CICIDS 2017, as well as the DNN model that performed well on KDDCup 99 are used to conduct the benchmark. Our DNN model trains a

关键词： Intrusion detection

来源：评论

学校读者我要写书评

暂无评论

Regional models for nonlinear system identification using the self-organizing map

Regional models for nonlinear system identification using th...

引用

13th international conference on intelligent data engineering and automated learning, ideal 2012

作者： De Souza Jr., Amauri H. Barreto, Guilherme A. Federal University of Ceará Department of Teleinformatics Engineering Center of Technology Av. Mister Hull S/N Fortaleza Ceará Brazil

ISBN: (纸本)9783642326387

Global modelling is a common approach to the problem of learning nonlinear dynamical input-output mappings. It consists in training a single multilayer neural network model using the whole dataset. On the other side of the spectrum stands the local modelling approach, in which the input space is divided into very small partitions and simpler (e.g. linear) models are trained, one per partition. In this paper, we propose a novel approach, called Regional Models (RM), that stands in between the global and local modelling ones. By following the approach by Vesanto and Alhoniemi [11], we first partition the input-output space using the Self-Organizing map (SOM), and then perform clustering over the prototypes of the trained SOM in order to find clusters of prototypes. Finally, a regional model is built for each cluster using the data vectors mapped to that cluster. the proposed approach is evaluated on two benchmarking problems and its performance is compared to those achieved by standard global and local models. © 2012 Springer-Verlag.

关键词： Self organizing maps

来源：评论

学校读者我要写书评

暂无评论

11th EAI international conference on Game theory for Networks, GameNets 2022

11th EAI International Conference on Game Theory for Network...

引用

11th EAI international conference on Game theory for Networks, GameNets 2022

ISBN: (纸本)9783031231407

the proceedings contain 25 papers. the special focus in this conference is on Game theory for Networks. the topics include: Design and Implementation of Targeted Poverty Alleviation System Based on Blockchain Network;an Intent-Based Routing Scheme in Satellite IoT;interference Management in Terrestrial-Satellite Networks Using Stackelberg Game;optimal Resource Allocation for Computation Offloading in Maritime Communication Networks: An Energy-Efficient Design via Matching Game;game theoretic Analysis of Resource Allocation in Multi-tiered Networks;Energy-Efficient Multi-cell NOMA Design via Coalition Formation Game;the Vaccination Game in Susceptible-Infected-Susceptible (SIS) Networks with Multipopulations;a Stochastic Bandwidth Scanning Game;port Capacity Leasing Games at Internet Exchange Points;multi-service Communication Isolation of Underground Pipe Gallery Based on WiFi6;a Phase Transition in Large Network Games;dynamic Pricing for Tenants in an automated Slicing Marketplace;service Function Chain Placement in Cloud data Center Networks: A Cooperative Multi-agent Reinforcement learning Approach;the Art of Concession in General Lotto Games;providing Slowdown Information to Improve Selfish Routing;budgeted Adversarial Network Resource Utilization Games;MU-PDR: A Method of Fingerprint Passive Positioning for WiFi6 Based on MU-RTS/CTS;the Optimal Layer of User-Specific Reconfigurable intelligent Surfaces Structure for Uplink Communication System;a Sophisticated Anti-jamming Strategy for a Joint Radar and Communication System;power data Credible Decision-Making Mechanism Based on Federated learning and Blockchain;a Service Protection Mechanism of Deterministic Networking Based on Segment Routing;cloud-Edge Collaboration Based Power IoT Scene Perception Mechanism;task Allocation Mechanism of Power Internet of things Based on Edge Routing Optimization.

关键词：

来源：评论

学校读者我要写书评

暂无评论

11th Mining Humanistic data Workshop, MHDW 2022, 7th 5G-Putting Intelligence to the Network Edge Workshop, 5G-PINE 2022, 1st workshop on AI in Energy, Building and Micro-Grids, AIBMG 2022, 1st Workshop/Special Session on Machine learning and Big data in Health Care, ML@HC 2022 and 2nd Workshop on Artificial Intelligence in Biomedical engineering and Informatics, AIBEI 2022 held as parallel events of the 18th IFIP WG 12.5 international conference on Artificial Intelligence Applications and Innovations, AIAI 2022

11th Mining Humanistic Data Workshop, MHDW 2022, 7th 5G-Putt...

引用

11th Mining Humanistic data Workshop, MHDW 2022, 7th 5G-Putting Intelligence to the Network Edge Workshop, 5G-PINE 2022, 1st workshop on AI in Energy, Building and Micro-Grids, AIBMG 2022, 1st Workshop/Special Session on Machine learning and Big data in Health Care, ML@HC 2022 and 2nd Workshop on Artificial Intelligence in Biomedical engineering and Informatics, AIBEI 2022 held as parallel events of the 18th IFIP WG 12.5 international conference on Artificial Intelligence Applications and Innovations, AIAI 2022

ISBN: (纸本)9783031083402

the proceedings contain 35 papers. the special focus in this conference is on Mining Humanistic data. the topics include: Digitally Assisted Planning and Monitoring of Supportive Recommendations in Cancer Patients;CAIPI in Practice: Towards Explainable Interactive Medical Image Classification;a Deep Q Network-Based Multi-connectivity Algorithm for Heterogeneous 4G/5G Cellular Systems;simulating Blockchain Consensus Protocols in Julia: Proof of Work vs Proof of Stake;Maximum Likelihood Estimators on MCMC Sampling Algorithms for Decision Making;employing Natural Language Processing Techniques for Online Job Vacancies Classification;Probabilistic Quantile Multi-step Forecasting of Energy Market Prices: A UK Case Study;proactive Buildings: A Prescriptive Maintenance Approach;performance Meta-analysis for Big-data Univariate Auto-Imputation in the Building Sector;non-intrusive Diagnostics for Legacy Heat-Pump Performance Degradation;a 5G-Based Architecture for Localization Accuracy;anomaly Detection in Small-Scale Industrial and Household Appliances;an Innovative Software Platform for Efficient Energy, Environmental and Cost Planning in Buildings Retrofitting;deep learning-Based Segmentation of the Atherosclerotic Carotid Plaque in Ultrasonic Images;An intelligent Grammar-Based Platform for RNA H-type Pseudoknot Prediction;An automated 2D U-Net Segmentation Method for the Identification of Cancer Brain Metastases Using MRI Images;the Use of Robotics in Critical Use Cases: the 5G-ERA Project Solution;fundamental Features of the Smart5Grid Platform Towards Realizing 5G Implementation;experimentation Scenarios for Machine learning-Based Resource Management;efficient data Management and Interoperability Middleware in Business-Oriented Smart Port Use Cases;5G for the Support of Smart Power Grids: Millisecond Level Precise Distributed Generation Monitoring and Real-Time Wide Area Monitoring;monitoring Neurological Disorder Patients via Deep learning Based Facial Expressions An

关键词：

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：