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检索条件"任意字段=2023 International Conference on Algorithms, Computing and Data Processing, ACDP 2023"

共 6946 条记录，以下是681-690 订阅

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Evolution of the Online Rating Platform data Structures and its Implications for Recommender Systems 3

Evolution of the Online Rating Platform Data Structures and ...

引用

3rd international conference on Applied Mathematics, Modelling, and Intelligent computing, CAMMIC 2023

作者： Wang, Hao Ratidar Technologies LLC Beijing China

ISBN: (数字)9781510667617

ISBN: (纸本)9781510667600

Online rating platform represents the new trend of online cultural and commercial goods consumption. The user rating data on such platforms are foods for recommender system algorithms. Understanding the evolution pattern and its underlying mechanism is the key to understand the structures of input data for recommender systems. Prior research on input data analysis for recommender systems is quite limited, with a notable exception in 2018 [6]. In this paper, we take advantage of Poisson Process to analyze the evolution mechanism of the input data structures. We discover that homogeneous Poisson Process could not capture the mechanism of user rating behavior on online rating platforms, and inhomogeneous Poisson Process is compatible with the formation process. © 2023 SPIE.

关键词： Recommender systems

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Smart Grid Privacy Via Differential Privacy Of Smart Metering data 3

Smart Grid Privacy Via Differential Privacy Of Smart Meterin...

引用

3rd international conference on computing and Information Technology, ICCIT 2023

作者： Almaleh, Abdulaziz Lahiq, Shatha Al-Shehri, Fatima King Khalid University College of Computer Science Abha Saudi Arabia King Khalid University Information Security Abha Saudi Arabia

ISBN: (纸本)9798350321487

The information collected by smart meters may be used in several ways. The collection and analysis of this data needed a substantial amount of time and money for the development of the smart grid. Despite the potential advantages of smart meters, the dissemination of such data could have a considerable effect on the lack of privacy. Implementing algorithms for power analysis to gather and disclose a user's personal information and interests based on the amount of power the user consumes has shown this. To protect the privacy of customers, we recommend using a differential privacy model for data aggregation after the collection of data by smart meters. To demonstrate this, we have used the Laplace mechanism to the row records of the smart meters, which protects the confidentiality of customer information. © 2023 IEEE.

关键词： Smart meters

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Automating News Tweet Writing Based on Indonesia Language Using NLG Approach 1

Automating News Tweet Writing Based on Indonesia Language Us...

引用

1st IEEE international conference on Cryptography, Informatics, and Cybersecurity, ICoCICs 2023

作者： Christina Aulia, Indra Purnamawati, Sarah University of North Sumatra Faculty of Computer Science and Information Technology Department of Information Technology Medan Indonesia Telkom University School of Computing Jakarta Indonesia

ISBN: (纸本)9798350339437

Over time, after the advent of the internet, the dissemination of news media has undergone developments ranging from websites to social media. However, news posted on social media is still written by reporters and undergoes editorial checks, resulting in a relatively long news processing time for posting. Therefore, to overcome these limitations, this research proposes an NLG (Natural Language Generation) approach using LSTM algorithms to assist in processing news data obtained from reporters into news tweets in the Indonesian language with the system called Automated Sports News Tweet Generator (ASNTG). The study's findings highlight the effectiveness of this method in generating news tweets sourced directly from on-location reporters through a Telegram chatbot. By doing so, it enables the production of real-time news updates, allowing readers to stay promptly informed about the latest events. Furthermore, the generated news tweets exhibit excellent naturalness aspects, as assessed by social media users and language experts who participated as respondents. © 2023 IEEE.

关键词： data handling

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A Comparison of data Mining Approaches for Forecasting Sales of FMCG Food Products 14

A Comparison of Data Mining Approaches for Forecasting Sales...

引用

14th international conference on computing Communication and Networking Technologies, ICCCNT 2023

作者： Doshi, Milan Atmiya University Computer Application Rajkot India

ISBN: (纸本)9798350335095

Sale forecasting is considered a key factor for balancing risk of over-stocking and out-of-stock. Its performance is largely influenced by the input it provides to supply chain activities. A competitive advantage for producers and retailers is the ability to predict sales of fast-moving consumer goods with greater accuracy, particularly in the food industries. If the accuracy of the sale prediction is poor, even with significant effort and financial investment, supply chain activities will still be unreliable and inefficient. The objective of the study is to evaluate the effectiveness of various data mining algorithms for predicting the future sales of FMCG food products. The study analyses four popular data mining techniques: Cluster Analysis, Regression Analysis, Visualization and Tracking Patterns on a dataset of historical sales data. The study compares the accuracy and efficiency of these algorithms using various performance metrics. The research aims to help the different stakeholders, like various businesses were involved in wholesale, manufacturing, marketing, logistics, and retailing. This study provides valuable insights for FMCG food product sales forecasting, and can be useful for businesses to make informed decisions about their sales strategies. © 2023 IEEE.

关键词： Sales

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Prediction of Crime data using Machine Learning Techniques 2

Prediction of Crime Data using Machine Learning Techniques

引用

2nd international conference on Sustainable computing and data Communication Systems, ICSCDS 2023

作者： Rao, P.Varaprasada Sunkari, Sukesh Raghumandala, Tejeshwararao Koka, Ganesh Rayankula, Deepak Chowdary Gokaraju Rangaraju Institute of Engineering & Technology Department of CSE Hyderabad India

ISBN: (纸本)9781665491990

Crime has a devastating effect on society and can take many forms, ranging from violent acts such as murder and assault to less serious but still damaging offenses like burglary and vandalism. Crime records are records of various criminal activities in a given area. These records typically include information such as the date, time, and location of reported crime, the nature of the crime, and the name of the suspect. However, there are many problems associated with keeping accurate and up-to-date records of criminal activity. The most common issue is a lack of uniformity in the way different states and municipalities track and record criminal activities. Additionally, many states and municipalities lack the resources to properly maintain accurate records, resulting in incomplete or inaccurate information. Finally, maintaining crime records is time consuming and expensive, leading to a backlog in the processing of reported crimes. This can complicate investigations and create a backlog of cases that need to be addressed. Therefore, this study proposes a model with an objective to make criminal investigation more effective. The two main facets of this research are crime analysis and prediction. Based on these aspects the datasets which contain all the data is pre-processed using different pre-processing techniques. Further, the dataset is processed using machine learning algorithms like Support Vector Machine, Random forest classifier, Decision tree, and K-Means. In conclusion, crime data analysis and prediction can provide valuable insights into criminal activity and aid in the development of effective crime prevention strategies. © 2023 IEEE.

关键词： Decision trees

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Trusted computing data Transaction Scheme based on Blockchain 7

Trusted Computing Data Transaction Scheme based on Blockchai...

引用

7th international conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2023

作者： Fanchang, Fanchang Yadav, Amit Khan, Asif Azam, Sami Yadav, Dakshina Chengdu Neusoft University Department of Software Engineering Chengdu China Integral University Department of Computer Application Lucknow India Charles Darwin University College of Engineering It and Environment NT Australia Charles Darwin University College of Engineering It and Environment Darwin Australia Plant Industry Department of Industry Tourism and Trade Line Darwin Australia

ISBN: (纸本)9798350341485

A blockchain technology based on encryption algorithm is proposed to address the issue of data theft and leakage in data transactions. Use blockchain to record transaction information and confirm the rights of data assets and sources;Use trusted computing and encryption algorithms to ensure data transmission security;After the data provider and demander complete the trusted calculation, the encrypted data results are returned. This scheme can perform data calculations without exposing the data to the data requester, and ensure transmission security through trusted encryption. © 2023 IEEE.

关键词： Blockchain

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Issues and Challenges of KDD Model for Distributed data Mining Techniques and Architecture 10

Issues and Challenges of KDD Model for Distributed Data Mini...

引用

17th INDIACom;2023 10th international conference on computing for Sustainable Global Development, INDIACom 2023

作者： Waseem, Mohammad Abidin, Shafiqul Aligarh Muslim University Department of Computer Science Aligarh India

ISBN: (纸本)9789380544472

We are currently seeing a data explosion and witnessing a meteoric rise in database sizes;therefore, with the widespread availability of such large volumes of data, there has arisen an urgent need to transform it into actionable insights and knowledge. So, data mining is a very important tool. The knowledge that is produced is put to use in a wide variety of contexts, containing but not limited to the following: science, technology, engineering, commerce, study, social, health, education, entertainment, etc. Market analysis, client retention, and production control are just some of the many uses for the knowledge gained from data. In this study, we explore the systems, methodologies, techniques, and algorithms for Distributed data Mining that may be used to effectively and efficiently deal with distributed data and extract useful insights. Moreover, some selected KDD models for Distributed data Mining have been systematically reviewed. © 2023 Bharati Vidyapeeth, New Delhi.

关键词： data mining

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Evaluating Off-chain Transaction Queueing Delay to Ensure data Integrity by Blockchain 8

Evaluating Off-chain Transaction Queueing Delay to Ensure Da...

引用

8th international conference on Cloud computing and Big data Analytics (ICCCBDA)

作者： Seike, Hirotsugu Aoki, Yasukazu Koshizuka, Noboru Hitotsubashi Univ Ctr Promot Social Data Sci Educ & Res Tokyo Japan Univ Tokyo Interfac Initiat Informat Studies Tokyo Japan Picolab Co LTD Tokyo Japan YRP Ubiquitous Networking Lab Tokyo Japan

ISBN: (纸本)9781665455336

In recent years, society has been promoting the use of big data to improve our daily lives. At the same time, there is a demand to verify the legitimacy of data. For this reason, there have been many proposals to ensure data integrity by a blockchain consensus. However, the blockchain-based system cannot process a lot of transactions in a short period. Therefore, the blockchain technology cannot be simply applied into systems where large amounts of data are added and updated. Off-chain protocols have been proposed to scale blockchains. They guarantee the integrity of data outside the blockchain and reduce the on-chain replication cost by not directly storing data in the blockchain storage. Meanwhile, an off-chain queueing delay is newly introduced since off-chain transactions (OTXs) are processed in a batch manner by periodically posting the OTX summary data on the underlying blockchain. This delay cannot be ignored, especially in the case of frequently updated data, such as IoT data. In this paper, we propose and analyze a queueing model that considers OTX processing time in order to estimate the mean OTX queueing delay. This analytical values help us to previously determine whether the adopted off-chain approach is effective to ensure the integrity of the given data. In numerical examples, we show how the parameters, such as the OTX batch size and the OTX rate, affect the OTX queueing delay.

关键词： blockchain scalability queueing model processing time high frequency data

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Research on Intelligent Communication data Transmission Security System Based on Computer Vision

Research on Intelligent Communication Data Transmission Secu...

引用

2023 IEEE international conference on Image processing and Computer Applications, ICIPCA 2023

作者： Dong, Yirui School of Computing National University of Singapore COM1 Department of Computer Science 13 Computing Drive Singapore117417 Singapore

ISBN: (纸本)9798350314670

This paper designs a new overall architecture of computer vision-based protection and monitoring system. The consistency between the design and DI&C-ISG-04 is analyzed. Three copy storage architecture is used to realize data security storage. In terms of secure transmission, Open VPN technology is used to establish secure network transmission channel. Digital certificate authentication is adopted to realize the data interaction between Intranet and extranet. In terms of network security, network security devices are deployed in accordance with the requirements of equal protection Level 3 to protect against external and internal network attacks. The test results show that data CAN be transmitted reliably through CAN data bus in fuse electronic safety system. This method can overcome the disadvantages of point-to-point communication system effectively, not only has higher information transmission rate, transmission capacity and adaptability, but also improves the utilization rate of resources. © 2023 IEEE.

关键词： Network security

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What to predict from Twitter data? 3

What to predict from Twitter Data?

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3rd international conference on computing and Information Technology, ICCIT 2023

作者： Salemdeeb, Mohammed Sahmoud, Shaaban Istanbul Sabahattin Zaim University Electrical-Electronics Engineering Istanbul Turkey Fatih Sultan Mehmet Vakif University Computer Engineering Department Istanbul Turkey

ISBN: (纸本)9798350321487

In the last decade, Twitter data has become one of the most valuable research sources for many areas including health, marketing, security, and politics. Researchers prefer Twitter data since it is completely public and can be easily downloaded using Twitter APIs. The recent intensive use of Twitter data makes it difficult for researchers to follow or analyze its research. In this paper, we summarize most of the predictable patterns, aspects, and attitudes from Twitter data and analyze the performance and feasibility of the algorithms used. Moreover, we describe the current popular Twitter datasets used in various domains and applications. Current challenges and research gaps are discussed, and some recommendations are given for future works from different perspectives. © 2023 IEEE.

关键词： Predictive analytics

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