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检索条件"任意字段=3rd International Conference on Machine Learning and Computer Application, ICMLCA 2022"

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machine learning for Sentiment Analysis and Classification of Restaurant Reviews 3

Machine Learning for Sentiment Analysis and Classification o...

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3rd international conference on Computing, Analytics and Networks, ICAN 2022

作者： Patil, Ratna Shukla, Divyanshu Kumar, Abhijeet Rajanak, Yutika Pratap Singh, Yadvendra Noida Institute Engineering of and Technology AIML Department Uttar Pradesh Greater Noida India Computer Science Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India Computer Science and Engineering Department Manipal University Jaipur Rajasthan Jaipur India

ISBN: (纸本)9781665499446

In this study, we performed sentiment analysis on restaurant reviews. To dine, we all go to restaurants with our loved ones and friends. However, we decide which restaurant to eat at before going there. Consequently, we select restaurants based on the reviews left by previous customers. A restaurant is a business, and the owner welcomes feedback from diners regarding their dining experiences so they may adjust their menu and amenities accordingly. Sentiment analysis is used to categories reviews as either good or negative, depending on whether they will have an impact on other people. Sentiment Analysis uses a machine learning algorithm and natural language processing to determine if a review is good or negative. It aids in the careful investigation of a scenario or service's good and negative effects, allowing for the suggestion of modifications. Both in terms of increasing consumer satisfaction and the caliber of the services offered, this might be advantageous. The user experience will be better as a result. This paper offers a study of key factors that distinguish between favorable and unfavorable assessments. This paper analyses various machine learning techniques that successfully analyze these reviews. In this study, we employed K-nearest neighbours Classifier, Logistic Regression, Support Vector Classifier (Gaussian NB and Multinomial NB), and Naive Bayes algorithm. A dataset from Kaggle was used in this study. Here, we will be able to observe which machine learning (ML) methods, can give more accurate results. We will also be able to evaluate how well an NLP can predict a sentiment from the given text. By illustrating how computers attempt to comprehend human sentiments, this article examines the possibilities. Out of everything, SVM produced an accuracy of 78 percent. © 2022 IEEE.

关键词： Sentiment analysis

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application of AI Intelligent learning System in Multimedia Demonstration 3

Application of AI Intelligent Learning System in Multimedia ...

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3rd international conference on machine learning and Big Data Analytics for IoT Security and Privacy, SPIoT2023

作者： Wang, Chen College of Education and Science Northwest Normal University Gansu Lanzhou730070 China Department of Public Security Gansu Police Vocational College Gansu Lanzhou730046 China

In order to adapt to the needs of the times, many enterprises have combined AI (Artificial Intelligence) technology with enterprise management to enhance their competitiveness, which is also essential in the field of education. This article attempted to integrate AI technology into multimedia teaching to improve the teaching quality of teachers and students' understanding of knowledge. The experiment found that AI technology could effectively improve students' understanding of knowledge points and also improve the clarity of knowledge point explanations during the teaching process. It could be seen that using AI intelligent learning systems for multimedia demonstrations could greatly improve the teaching quality of teachers, as well as the learning interest and effectiveness of students. © 2023 The Authors. Published by Elsevier B.V.

关键词： learning systems

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Comparative Analysis of Suspicious Activity Detection Techniques in Surveillance Videos 3

Comparative Analysis of Suspicious Activity Detection Techni...

引用

3rd international conference on Disruptive Technologies, ICDT 2025

作者： Kumar, Prabhakar Singh, Sahil Raza, Md. Tahseen Arora, Yojna Sharda University Department of Computer Science and Technology Greater Noida India

ISBN: (纸本)9798331519582

The need to detect suspicious activities automatically in surveillance videos has become a significant challenge in recent time and became a hot topic for researchers to find and develop new and better techniques to solve this problem. This paper provides a detailed review of several papers and the methods used in those on anomaly detection in video surveillance using different machine learning and deep learning techniques which have been explored till now and gave promising results. CNN-based models, spatiotemporal autoencoders, object-centric autoencoders, and transfer learning-based algorithms are among the approaches examined in this paper. A comparative review of their techniques, accuracy, computing efficiency, and real-time application is presented. © 2025 IEEE.

关键词： Deep learning

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Effective Location-based Recommendation Systems for Holiday using RBM machine learning Approach 3

Effective Location-based Recommendation Systems for Holiday ...

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3rd international conference on Artificial Intelligence and Smart Energy, ICAIS 2023

作者： Jayaraman, Ramkumar Karthikeyan, C. Sahaya Anselin Nisha, A. Somasundaram, K. Naga Saranya, N. Vijendra Babu, D. Srm Institue of Science and Technology Department of Computing Technology Tamil Nadu Kattankulathur India Koneru Lakshmaiah Education Foundation Computer Science and Engineering Andhra Pradesh Vaddeswaram India Sathyabama Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India Institute of Information Technology Saveetha School of Engineering Simats Tamil Nadu Chennai India Meenakshi College of Engineering Departement of Mca Tamil Nadu Chennai India Vellore Institute of Technology School of Electronics Engineering Tamil Nadu Vellore India

ISBN: (纸本)9781665462167

application developers and researchers took many steps in finding out proper tourism recommendations for various seasons. With the faster development in the travel department through modern technologies, it has gotten fundamental to present headways and upgrades in the administrations given to the sightseers, to ensure their ease of travel and satisfaction. Over the years, there has been no optimal system providing all the necessities required by a tourist. Based on the holidata recommendation, proposed system makes to decrease the time spent on the planning period and it helps to increase the deployment of process to be more effective. Regarding the customer preferences, the customer details and their location are shared and there are some other information available based on the users are, their destination trip, dates for the travel, budget and there are other user attractive aspects as it helps to have the effective trip. Based on the above things, the travel can be planned for the trip entirely. This system uses RBM to predict the user ratings and recommend the best attraction. An attempt has been made to reduce the MAE in RBM prediction. © 2023 IEEE.

关键词： Budget control

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application of Ecological Energy Saving Design in Building Reconstruction Project 3

Application of Ecological Energy Saving Design in Building R...

引用

3rd international conference on machine learning and Big Data Analytics for IoT Security and Privacy, SPIoT2023

作者： Nie, Kun Architecture and Environmental Engineering Dongying Vocational Institute Shandong Dongying China

Construction is an indispensable part of people's life. The development of the construction industry is naturally overwhelming. In addition, the improvement of people's living standards has led to the rapid shortage of building resources and the increasingly serious energy problem. In fact, traditional buildings constructed by traditional building technologies are almost all high energy consumption, which has led to a sharp reduction of non renewable resources. People have also gradually found this important problem. Therefore, the concept of application of ecological energy saving technology in building reconstruction has been proposed. On this basis, this paper analyzes the energy conservation design of the external environment of the building, the energy conservation design of doors and windows, the energy conservation design of the building wall and the energy conservation design of the roof through mathematical analysis. The final results show that the energy-saving architectural design concept can really avoid the waste of non renewable resources and improve people's living experience. © 2023 The Authors. Published by Elsevier B.V.

关键词： Energy conservation

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application of Improved Linear Regression Algorithm in Business Behavior Analysis 3

Application of Improved Linear Regression Algorithm in Busin...

引用

3rd international conference on machine learning and Big Data Analytics for IoT Security and Privacy, SPIoT2023

作者： Shi, Yue University of Sheffield Sheffield United Kingdom

Linear regression algorithm is a widely used model in business behavior analysis, aiming to explore the relationship between independent and dependent variables. However, traditional linear regression algorithms have issues with accuracy and time cost when dealing with large amounts of data. To address these issues, this article proposed an improved linear regression algorithm and applied it to business behavior analysis. In the experiment, the algorithm was applied to the sales data of an e-commerce company, including a total of 5000 sales records. A comparison was made between the traditional linear regression algorithm and the improved algorithm, and the results showed that the improved algorithm improved accuracy by 23% and reduced time cost by 18%. In addition, the improved algorithm can quickly process a large amount of data and better predict sales trends. The improved linear regression algorithm proposed in this article has great application potential in business behavior analysis, which can improve accuracy and efficiency, and provide more reliable support for business decision-making. © 2023 Elsevier B.V.. All rights reserved.

关键词： Sales

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3rd international conference on computer Science, Electrical and Electronic Engineering, ICCEE 2021

3rd International Conference on Computer Science, Electrical...

引用

3rd international conference on computer Science, Electrical and Electronic Engineering, ICCEE 2021

ISBN: (纸本)9789811697807

The proceedings contain 15 papers. The special focus in this conference is on computer Science, Electrical and Electronic Engineering. The topics include: Velocity-Based Control of Piston Trajectory in a Free-Piston Linear Electric Generator by Load Current Modulation;GBI-Based Wireless Home Automation System Using IoT;embedded machine learning on a Programmable Neuromorphic Platform;investigation on Two Dimensional Photonic Crystal Based All Optical Logic Gates;miniaturized Multiband Metamaterial Antenna for 5G applications;model-Based Testing of Access Control Requirement in Multi-tenant application: An Extensive Life Cycle;survivable Biconnected Topology for Yemen’s Optical Network;a Study on Electric Field Distribution in Polymeric Insulator Using Finite Element Method;Modelling and Simulation of Building-Integrated Photovoltaics (BIPV) Installations in Swinburne University;ant Colony Optimization Algorithms for Routing in Wireless Sensor Networks: A Review;Analyzing the Effects of Corona Ring Material and Dimensions on the Electric Field Distribution of 132 kV Glass Insulator String Using 2-D FEM;Ultra-Compact All-Optical NAND Logic Gates Based on 4 × 4 MMI Coupler Using Silicon Hybrid Plasmonic Waveguides;Microstrip Patch Antenna Arrays Design for 5G Wireless Backhaul application at 3.5 GHz.

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3D Image Reconstruction from Multi-View Images using the Encoder-based Feature Map Generation 3

3D Image Reconstruction from Multi-View Images using the Enc...

引用

3rd international conference on Smart Electronics and Communication, ICOSEC 2022

作者： Kamble, Tanaji Umaji Mahajan, Shrinivas Padmakar Arutwar, Shrikrishnakumar College of Engineering Pune Department of Electronics and Telecommunication Engineering Pune India Government Polytechnic College Lecturer at Department of Computer Engineering Maharashtra India

ISBN: (数字)9781665497640

ISBN: (纸本)9781665497640

The geometric feature of the image acquisition-based computer vision application utilizes the 3D image reconstruction for the required scene. The inaccurate reconstruction results and the enormous memory requirement limit the method's performance. The deep learning-based methods provide promising results with elevated accuracy for computer vision applications. Hence, this research introduces a novel framework based on the deep learning strategy for the 3D image reconstruction of objects from multiple view images. The encoder-decoder-fusion-refiner module is proposed for the image reconstruction, in which the encoder module is proposed to generate the feature map. The significant attributes are taken out from the input multi-view image using the ResNet-50 and AlexNet pre-trained models, and then the channel and spatial information are gathered for obtaining the feature map. The most significant attribute section helps to reduce the computation complexity and elevates the accuracy of the reconstruction process. The newly devised method is evaluated by considering measures like loss and Intersection over Union (IoU) and obtaining the values of 1.04E+00, 1.11E+00, and 2.12E-01 for IoU_3D, IoU_2D and loss, respectively. © 2022 IEEE.

关键词： Image reconstruction

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Enterprise Support Hierarchical Model with Secure Data Protocol 3

Enterprise Support Hierarchical Model with Secure Data Proto...

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3rd international conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Vinay Simha Reddy, T. Parvathi, S. Sarada, Ch. Mohmmed, Karrar Hatif Sampath Dakshina Murthy, A. Saikumar, K. Malla Reddy University Dept of Artificial Intelligence and Machine Learning Maisammaguda Hyderabad Telangana Dulapally India Mlr Institute of Technology Department of Computer Science and Information Technology Telangana Hyderabad India Cvr College of Engineering Department of Cse Telangana Hyderabad India Scientific Research Center Al-Ayen University Thi-Qar64001 Iraq Department of Ece Andhra Pradesh Duvvada India Koneru Lakshmaiah Education Foundation Dept of Cse Telangana Hyderabad500075 India

ISBN: (纸本)9798350319125

CHARON is a cloud-upheld capacity framework that can store and share large information in a manner that is protected, solid, and proficient. It does this by utilizing different cloud sources and capacity areas to meet the lawful prerequisites for private individual information. CHARON has three things that make it stick out: It doesn't require trust in any one individual or thing. It needn't bother with a client-oversaw server. It handles large records well across a bunch of putting-away administrations in various regions of the planet. We likewise made another Byzantine-strong information-driven rental plan to stay away from composing issues between clients utilizing shared documents. We test CHARON by displaying test processes from science, a notable huge information region, utilizing miniature and application-based measures. The outcomes show that our novel plan isn't just imaginable, however, it additionally stirs up to multiple times better compared to other cloud-based arrangements from beginning to end. © 2023 IEEE.

关键词： CHARON Cloud computing

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A Mechanism Design Approach for Multi-party machine learning

A Mechanism Design Approach for Multi-party Machine Learning

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3rd international Joint conference on Theoretical computer Science (IJTCS) / 16th international conference on Frontiers of Algorithmic Wisdom (FAW)

作者： Chen, Mengjing Liu, Yang Shen, Weiran Shen, Yiheng Tang, Pingzhong Yang, Qiang Tsinghua Univ Beijing Peoples R China WeBank Co Ltd Shenzhen Peoples R China Renmin Univ Beijing Peoples R China Duke Univ Durham NC USA Hong Kong Univ Sci & Technol Clear Water Bay Hong Kong Peoples R China

ISBN: (纸本)9783031207952;9783031207969

In a multi-party machine learning system, different parties cooperate on optimizing towards better models by sharing data in a privacy-preserving way. A major challenge in learning is the incentive issue. For example, if there is competition among the parties, one may strategically hide his data to prevent other parties from getting better models. In this paper, we study the problem through the lens of mechanism design and incorporate the features of multi-party learning in our setting. First, each agent's valuation has externalities that depend on others' types and actions. Second, each agent can only misreport a type lower than his true type, but not the other way round. We call this setting interdependent value with type-dependent action spaces. We provide the optimal truthful mechanism in the quasi-monotone utility setting. We also provide necessary and sufficient conditions for truthful mechanisms in the most general case. We show the existence of such mechanisms is highly affected by the market growth rate. Finally, we devise an algorithm to find the desirable mechanism that is truthful, individually rational, efficient and weakly budget-balance.

关键词： Mechanism design Federated learning Incentive design

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