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检索条件"任意字段=8th IEEE International Conference on Software Engineering and Computer Systems, ICSECS 2023"

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Sentiment Analysis of Amazon Product Reviews using VADER and RoBERTa Models 8

Sentiment Analysis of Amazon Product Reviews using VADER and...

引用

8th international conference on Communication and Electronics systems, ICCES 2023

作者： Hussain, Shadmaan Dhanda, Namrata Verma, Rajat Amity University Uttar Pradesh Department of Computer Science and Engineering Lucknow Campus India Pranveer Singh Institute of Technology Department of Computer Science and Engineering Uttar Pradesh Kanpur India

ISBN: (纸本)9798350396638

Natural language processing's rapidly expanding field of sentiment analysis seeks to extract subjective information from text data. this article offers a thorough overview of the most advanced lexicon-based, machine learning-based, and hybrid sentiment analysis methodologies. the study discusses the challenges and limitations of sentiment analysis, such as the lack of labelled data, the ambiguity of language, and ethical considerations. the study also presents a critical analysis of the current applications of sentiment analysis in various domains, including marketing, customer service, social media, healthcare, and politics. Furthermore, the research work highlights future directions and opportunities for research in the field, such as the development of more accurate sentiment analysis techniques, the integration of multimodal data, and the exploration of ethical and privacy implications. this study offers a thorough grasp of sentiment analysis, including its current applications, difficulties, and potential future research areas. © 2023 ieee.

关键词： Sentiment analysis

来源：评论

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Handwritten Text Recognition Using Machine Learning and Deep Learning 8

Handwritten Text Recognition Using Machine Learning and Deep...

引用

8th ieee international conference on Science, Technology, engineering and Mathematics, ICONSTEM 2023

作者： Ms, Sudarchanan Sujan, G. Akila Devi, R. Rajalakshmi Engineering College Computer Science and Engineering Chennai India

ISBN: (纸本)9798350347791

A new area of computer vision is character recognition. A common research topic is the growing use of digital and modern technologies in practically all industries and daily activities to store, transmit, and recognise handwritten characters for usage in digital formats. Any style of handwriting can be recognised by people. the handwritten transcription cannot be recognised by the machine. We require the computer to recognise the handwritten text because of this. A computer system may recognise and digitize handwritten input from sources including pictures, handwritten documents, and other sources of text by using handwritten character recognition. the development is based on a machine learning and artificial intelligence subfield known as deep learning. there are many different approaches and strategies used to construct handwritten character recognition systems. Yet, only few of them concentrate on neural networks. Compared to earlier methods, the use of neural networks for handwritten character recognition is more efficient. the Handwritten Character Recognition System is described in this system, along with its architecture, design, and testing procedures. the objective is to show how well neural networks recognise characters in handwritten text. In order to read handwritten notes from students and instructors, this system will report on the development of a handwritten character recognition system. this system turns a handwritten transcription's image into a digital text. © 2023 ieee.

关键词： Neural network models

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Machine Learning Based Yoga Recommendation System for the Physical Fitness 8

Machine Learning Based Yoga Recommendation System for the Ph...

引用

8th ieee international conference on Science, Technology, engineering and Mathematics, ICONSTEM 2023

作者： Baruah, Anganabha Koti, Valli Madhavi Pandey, Vivekanand Gungewale, Savita Mohan Reddy, N Srikanth Gupta, Monika Amity University Amity Institute of Psychology and Allied Sciences India Giet Degree College Department of Computer Science Rajahmundry India Amity University Bihar Patna India Shree Siddheshwar Women's College of Engineering Computer Science and Engineering Department Solapur India Presidency University Bangalore560064 India Chitkara University Chitkara Business School Punjab India

ISBN: (纸本)9798350347791

A recommendation system's goal is to expect client interests and derive their points of view. this system can furnish clients with the data they require in light of their necessities and keeping in mind that thinking about their inclinations. To improve recommendations, the information should be all the more completely dissected. At the point when individuals take in critical chilly, their safe systems can be hindered. At the point when there is no physical movement during the day, flu occasionally influences invulnerability and respiratory lot infection. Physical movement fortifies an individual's insusceptible system. the people who overchill are more inclined to infections since it requires more work to keep them at an ordinary internal heat level. this study made a system for anticipating physical fitness utilizing information on calorie consumption, race, orientation, inclinations, and medical issue. the proposed recommendation system makes practice recommendations in light of the client's inclinations while considering comorbidities, geographic areas, and exercise and eating ways of behaving. © 2023 ieee.

关键词： Recommender systems

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Scientific Paper Recommendation System 8

Scientific Paper Recommendation System

引用

8th ieee international conference for Convergence in Technology, I2CT 2023

作者： Singh, Rajeev Gaonkar, Gaurav Bandre, Vedant Sarang, Nishant Deshpande, Sachin Computer Engineering Vidyalankar Institute of Technology University of Mumbai Mumbai India

ISBN: (纸本)9798350334012

Advancements in research and technology have resulted in a flood of information in scientific research areas. It is challenging to find research papers of interest in today's scenario, where hundreds of articles are published daily. It makes it impossible for the researcher and other readers to keep abreast of the research in their domain. Previously keyword matching techniques and recommender systems were used for finding relevant research papers. But these approaches were time-consuming and failed in scaling for a large dataset containing millions of articles. In this research, we propose a scalable end-to-end content-based scientific paper recommendation system capable of recommending research papers from the abstract or the context of the research paper for which we want to find the recommendation. We also evaluate our system using the average co-citation metric from [1]. Our end-to-end system performs with a average co-citation score of 14.88 and has an average response time of 1.4 seconds. © 2023 ieee.

关键词： Recommender systems

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Recommendation System using NLP and Collaborative Filtering 8

Recommendation System using NLP and Collaborative Filtering

引用

8th ieee international conference for Convergence in Technology, I2CT 2023

作者： Shah, Dhvani Shokeen, Chinmay Khanzode, Shantanu Kale, Pranav Kn, Divyaprabha PES University Computer Science Engineering Bangalore India

ISBN: (纸本)9798350334012

A significant amount of online shopping has been observed during the pandemic. Surveys suggest that 20-30% more businesses are moving online in response to the pandemic. the goal was to develop an apparel e-commerce website that is also tailored to the individual using Natural Language Processing and Collaborative Filtering algorithms, thereby recommending items based on what they choose. In the current system, the market uses a collaborative filtering and content-based filtering, hybrid model. We aimed to resolve the cold start problem that persists in many of the current e-commerce websites. the recommendation engine is based on the input given by the pre-trained Natural Language Processing model, where the items from the dataset are segregated into broad themes based on the product description. these themes are then put into clusters based on their similarity. the recommendation engine uses collaborative filtering and picks up similar products from the clusters formed to provide the users with appropriate recommendations. © 2023 ieee.

关键词： Recommender systems

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software Metrics for Container-Based Applications: Systematic Literature Review 8

Software Metrics for Container-Based Applications: Systemati...

引用

8th international conference on Information Management and Technology, ICIMTech 2023

作者： Al Qausar, Muhammad Juan Soeparno, Haryono Gaol, Ford Lumban Arifin, Yulyani Bina Nusantara University Binus Graduate Program - Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350326093

Containerization has become a popular approach in application development in applications development and deployment, many benefits we can get such as improved scalability, portability, and resource efficiency. Container-based applications, utilizing technologies like Docker and Kubernetes, have transformed the packaging, deployment, and management of software from the desktop environment to the cloud platform. In this context, software metrics approach plays a good role in evaluating the characteristics and performance of container-based applications, ensuring that developers and operators are on the same page. this article explores the importance of software metrics in optimizing the software lifecycle of container-based applications, addressing the unique challenges they present, and highlighting the potential benefits of leveraging metrics to improve performance and efficiency. Our finding Performance Metrics and Availability Metrics is the most metrics that the most measure by applications owner, relevant studies and industry practices, this study aims to provide insights and recommendations to effectively measure and optimize region-based software systems. © 2023 ieee.

关键词： Containers

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Efficient Device Management for Enhanced Energy Utilization and Operational Performance in Internet of things 8

Efficient Device Management for Enhanced Energy Utilization ...

引用

8th ieee international conference for Convergence in Technology, I2CT 2023

作者： Jose, Basil Romi Mini, S. National Institute of Technology Goa Department of Computer Science and Engineering Goa 403401 India

ISBN: (纸本)9798350334012

the Internet of things is a rapidly growing field, and the management of IoT nodes is becoming increasingly important. Perpetual energy supply remains a major area of concern for IoT devices. IoT nodes with low energy levels may go into a sleep state, making them unavailable for use and they must be recharged to be reused. the challenge is to select the nodes that should be charged to minimize downtime and maximize uptime. this paper proposes the use of the Gur game algorithm to optimize the management of IoT nodes for maximum uptime and minimum downtime. the Gur game algorithm is used to proactively select the nodes to be charged, considering the current energy levels of the nodes and the utilization of IoT nodes in the network. A preliminary result is proposed in this paper. the proposed method is a unique approach in managing IoT nodes, providing an effective way to ensure optimal utilization of resources and efficient operation of IoT systems. © 2023 ieee.

关键词： Internet of things

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A Contemporary Method of Assessing Water Quality based on the Fusion of Predictive Analytics and Deep Structured Learning 8

A Contemporary Method of Assessing Water Quality based on th...

引用

8th international conference on Communication and Electronics systems, ICCES 2023

作者： Manoj, Rahan Abhishek, S. Nair, Bharath Prathap Anjali, T. Ramlal, Nandakishor Prabhu Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Amritapuri India Altair Engineering Inc Cse India

ISBN: (纸本)9798350396638

the human activities that cause untreated wastewater, sewage water, and rubbish to contaminate water bodies pose a danger to natural water supplies. Monitoring water quality is essential for protecting water resources and ensuring that only clean water is available for consumption. this study assesses the performance of several machine learning methods, including deep learning models, support vector machines, Naive Bayes, K-Nearest Neighbours, Decision Trees, Random Forests, and Logistic Regression. the findings show that Random Forests performed better than other machine learning methods, with an accuracy of 79.6093%. With an accuracy of 70.9402%, deep learning models also demonstrated encouraging results. © 2023 ieee.

关键词： Water quality

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Knowledge-Based Medical Tourism Recommender System 8

Knowledge-Based Medical Tourism Recommender System

引用

8th ieee international conference for Convergence in Technology, I2CT 2023

作者： Harinivas, Aishwarya Bharathi, R. Gowda, Chetan A Mohata, Priya Sharmila, R. PES University Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350334012

Medical tourism refers to people travelling to other countries to access cost-effective and high-quality medical treatment. Over the past few years, the need for medical tourism has increased due to a lack of infrastructure in the places they reside or financial aid. Although there are websites that provide information regarding hospitals and their treatments, they employ basic filtration methods to present the results to the user. In order to address this problem, a medical tourism recommendation system was *** medical tourism recommendation system is knowledge-based. It leverages the data available to offer the best results for each treatment. Based on the user's requirements, the top-k recommendations are given using an aggregated score. the results have been validated and found to be satisfactory. the recommendation system would definitely benefit users who need to travel for their medical assistance and cater to their budget-friendliness and high-quality treatment requirements. © 2023 ieee.

关键词： Recommender systems

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Virtual Instrument for Recognition of *** Infected Corn Seeds Based on Color Image Analysis and Labview 8

Virtual Instrument for Recognition of *** Infected Corn Seed...

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8th international conference on Big Data, Knowledge and Control systems engineering, BdKCSE 2023

作者： Dimitrova, Georgieva Tzvetelina Stefanova, Kirilova Eleonora Ivanov, Daskalov Plamen Kiril, Tenekedjiev University of Ruse Department of Automatics and Mechatronics Ruse Bulgaria N.Y.Vaptsarov Naval Academy Department of Information Technologies Varna Bulgaria

ISBN: (纸本)9798350313246

A virtual instrument for color image analysis of sound and infected with Fusarium Moniliforme corn seeds developed in LabView is presented in this paper. A modified approach for classification of seeds based on extracted features using Karhunen-Loeve transformation has been proposed. Classification of 16 varieties of corn by using different Bayesian classifiers, two types of linear classifiers - with an average weighted and average arithmetic covariance matrix, and quadratic classifiers is allowed by the instrument. Experimental results for 16 Bulgarian varieties are obtained and showed total error of 0.55 % - 6.9 % for control measurements of the seed sample. © 2023 ieee.

关键词： computer vision

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