Pub Date : 2021-12-01DOI: 10.1109/ICCS54944.2021.00050
Akeel Farooq, Privanka Chawla
According to Business Insider, computerized reasoning software would save banks and financial institutions $447 billion by 2023. According to Forbes, 70% of financial firms are using AI to predict revenue events, adjust financial evaluations, and detect extortion. According to Forbes, 54 percent of financial aid organizations with 5,000 or more employees use artificial intelligence. The recent FinTech surge shows the years of important breakthroughs and potentials of AI in creating a finance and society system that makes sense. In AI, data technology, economics, finance, and other relevant research processes and commercial domain names, AI-empowered economy and finance has been a suggested and area that is becoming increasingly vital. The new-generation AI, Data Machine, and technology learning, which are fundamentally and seamlessly transforming the eyesight, Missions, Objectives, paradigms, theories, approaches, tools, and social areas of economics and driving and finance smart FinTech, are adding to this long history of finance. AI continues to authorize more complicated mechanisms, such as economic financial products, replicas, facilities, organizations, and applications that are more complex than customized and enhanced, safe and fresher normal and other mechanisms. This review highlights the long-term study of AI in finance and focuses on establishing a complete, multidimensional, and problem-driven economic-financial research linked with the roles and research instructions of both classic and modern AI in finance.
{"title":"Review of Data Science and AI in Finance","authors":"Akeel Farooq, Privanka Chawla","doi":"10.1109/ICCS54944.2021.00050","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00050","url":null,"abstract":"According to Business Insider, computerized reasoning software would save banks and financial institutions $447 billion by 2023. According to Forbes, 70% of financial firms are using AI to predict revenue events, adjust financial evaluations, and detect extortion. According to Forbes, 54 percent of financial aid organizations with 5,000 or more employees use artificial intelligence. The recent FinTech surge shows the years of important breakthroughs and potentials of AI in creating a finance and society system that makes sense. In AI, data technology, economics, finance, and other relevant research processes and commercial domain names, AI-empowered economy and finance has been a suggested and area that is becoming increasingly vital. The new-generation AI, Data Machine, and technology learning, which are fundamentally and seamlessly transforming the eyesight, Missions, Objectives, paradigms, theories, approaches, tools, and social areas of economics and driving and finance smart FinTech, are adding to this long history of finance. AI continues to authorize more complicated mechanisms, such as economic financial products, replicas, facilities, organizations, and applications that are more complex than customized and enhanced, safe and fresher normal and other mechanisms. This review highlights the long-term study of AI in finance and focuses on establishing a complete, multidimensional, and problem-driven economic-financial research linked with the roles and research instructions of both classic and modern AI in finance.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133196253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-01DOI: 10.1109/ICCS54944.2021.00046
Rishabh Srivastava, D. Prashar
Security of data has been a necessity in this era and block-chain is emerging as the most secure and reliable platform in many sectors. One among them is the health care industry where we can optimize the daily life applications. Examination about block-chain and medical services is presently restricted, yet block-chain is near the very edge of changing the medical services framework; through its decentralized standards, block-chain can further develop openness and security of patient data, and can hence topple the medical care pecking order and construct another framework wherein patients deal with their own consideration. In this paper, we survey existing writing and applications accessible for the medical services framework utilizing block-chain innovation. Further we additionally propose a Secure Healthcare Management System utilizing Block-chain.
{"title":"A Secure Block-chain Enabled Approach for E-Heath-care System","authors":"Rishabh Srivastava, D. Prashar","doi":"10.1109/ICCS54944.2021.00046","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00046","url":null,"abstract":"Security of data has been a necessity in this era and block-chain is emerging as the most secure and reliable platform in many sectors. One among them is the health care industry where we can optimize the daily life applications. Examination about block-chain and medical services is presently restricted, yet block-chain is near the very edge of changing the medical services framework; through its decentralized standards, block-chain can further develop openness and security of patient data, and can hence topple the medical care pecking order and construct another framework wherein patients deal with their own consideration. In this paper, we survey existing writing and applications accessible for the medical services framework utilizing block-chain innovation. Further we additionally propose a Secure Healthcare Management System utilizing Block-chain.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":" 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120933568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-01DOI: 10.1109/ICCS54944.2021.00041
S. Paul, Salil Batra
Malaria Parasites are transferred from infected female mosquitos to humans which can lead to the death of the person. Malaria affects the majority of people each year, and most of these cases arise in remote areas. There has been lots of research in the field of Malaria Parasite detection using the automated technique, but these techniques require high computational power, and in remote areas, the availability of such systems is very unlikely. The proposed Ensemble Model can detect the presence of Malaria Parasite in the thick blood smear by taking the average of the output layers of ResNet50 and the custom CNN model. The models' performance has been evaluated and results reveal that it achieved 0.97 Specificity, 0.98 Sensitivity, 0.97 Precision, and 0.972 Accuracy with an image size of 64x64x3. The overall file size of the model is under 15Mb that also makes it portable.
{"title":"Stacked Ensemble Deep Learning Technique to Detect Malaria Parasite in Blood Smear","authors":"S. Paul, Salil Batra","doi":"10.1109/ICCS54944.2021.00041","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00041","url":null,"abstract":"Malaria Parasites are transferred from infected female mosquitos to humans which can lead to the death of the person. Malaria affects the majority of people each year, and most of these cases arise in remote areas. There has been lots of research in the field of Malaria Parasite detection using the automated technique, but these techniques require high computational power, and in remote areas, the availability of such systems is very unlikely. The proposed Ensemble Model can detect the presence of Malaria Parasite in the thick blood smear by taking the average of the output layers of ResNet50 and the custom CNN model. The models' performance has been evaluated and results reveal that it achieved 0.97 Specificity, 0.98 Sensitivity, 0.97 Precision, and 0.972 Accuracy with an image size of 64x64x3. The overall file size of the model is under 15Mb that also makes it portable.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116260228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-01DOI: 10.1109/ICCS54944.2021.00022
S. U. M. Reddy, N. Venkatesh, N. Nagendra, P. Prasad, M. R. Nayak
Recent trends in solar power generation such as solar panel design with consideration of light reflector arrangements pays more attention to enhance the solar panel efficiency compared to other methodologies such as maximum power tracking techniques (MPTT). All these existing maximum power tracking techniques are concentrated on the tracking of the sun direction to increase cell efficiency with the help of dynamic operation involvement. All these techniques are limited to attain a maximum or nearly maximum efficiency of the solar panel efficiency. The design concept of solar panels with light reflector arrangements provides enhanced solar cell efficiency compared to maximum power tracking (MPT) techniques with the static response of operation. Also, the stressed light reflection concept may provide significant support to extract maximum cell efficiency. This confirms that the design consideration of solar panels with light reflector arrangements compared to other MPT techniques results in enhanced solar panel efficiency. Not only the enhanced panel efficiency, but it also results in less maintenance cost due to no rotational parts are involved. But the major drawback of this type of arrangement is its aging problem of the solar panels. This light reflector arrangement generates concentrated heat generation on the solar panels which meet the cell temperature coefficient fast. Therefore, an alternative design modification to avoid this concentrated heat generation makes superior design considerations for the solar panels compared to existing panel designs. So, the authors are tried to propose the innovative methodology to obtain enhanced solar cell efficiency using the heatless light reflection method. Hence, this paper aims to discuss the alternative design modifications of solar panels with light reflector arrangements to nullify the aging problem of the panel and enhance the overall solar panel efficiency. Also, this paper presents the summary of the efforts carried out on the concept of solar panels with light reflector arrangements and its obtained outputs.
{"title":"Study On New Design Techniques for Enhancement of Solar Panel Efficiency","authors":"S. U. M. Reddy, N. Venkatesh, N. Nagendra, P. Prasad, M. R. Nayak","doi":"10.1109/ICCS54944.2021.00022","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00022","url":null,"abstract":"Recent trends in solar power generation such as solar panel design with consideration of light reflector arrangements pays more attention to enhance the solar panel efficiency compared to other methodologies such as maximum power tracking techniques (MPTT). All these existing maximum power tracking techniques are concentrated on the tracking of the sun direction to increase cell efficiency with the help of dynamic operation involvement. All these techniques are limited to attain a maximum or nearly maximum efficiency of the solar panel efficiency. The design concept of solar panels with light reflector arrangements provides enhanced solar cell efficiency compared to maximum power tracking (MPT) techniques with the static response of operation. Also, the stressed light reflection concept may provide significant support to extract maximum cell efficiency. This confirms that the design consideration of solar panels with light reflector arrangements compared to other MPT techniques results in enhanced solar panel efficiency. Not only the enhanced panel efficiency, but it also results in less maintenance cost due to no rotational parts are involved. But the major drawback of this type of arrangement is its aging problem of the solar panels. This light reflector arrangement generates concentrated heat generation on the solar panels which meet the cell temperature coefficient fast. Therefore, an alternative design modification to avoid this concentrated heat generation makes superior design considerations for the solar panels compared to existing panel designs. So, the authors are tried to propose the innovative methodology to obtain enhanced solar cell efficiency using the heatless light reflection method. Hence, this paper aims to discuss the alternative design modifications of solar panels with light reflector arrangements to nullify the aging problem of the panel and enhance the overall solar panel efficiency. Also, this paper presents the summary of the efforts carried out on the concept of solar panels with light reflector arrangements and its obtained outputs.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123411948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-01DOI: 10.1109/ICCS54944.2021.00015
Abhishek Goyal, Rakesh Garg, K. Bhatia
Cloud computing is one of the fastest evolving technologies and is the future in computing for companies looking for technological updation, more productivity and service providers are seeking enhanced revenue. Information technology services and infrastructure are outsourced so to make them remotely accessible through internet. Organizations utilizing cloud-computing services and models have a competitive edge to their counterparts. Different cloud service & deployment models and strategies have been developed in due course of time with the growing demand. This alarming development leads to few challenges as well like security issues, compliance, cost, expertise, performance and managing multiple clouds and its migration. Cloud computing models are discussed and its challenges are bifurcated into two broad categories technical and managerial aspects.
{"title":"Models and Challenges Categorization in Cloud Computing","authors":"Abhishek Goyal, Rakesh Garg, K. Bhatia","doi":"10.1109/ICCS54944.2021.00015","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00015","url":null,"abstract":"Cloud computing is one of the fastest evolving technologies and is the future in computing for companies looking for technological updation, more productivity and service providers are seeking enhanced revenue. Information technology services and infrastructure are outsourced so to make them remotely accessible through internet. Organizations utilizing cloud-computing services and models have a competitive edge to their counterparts. Different cloud service & deployment models and strategies have been developed in due course of time with the growing demand. This alarming development leads to few challenges as well like security issues, compliance, cost, expertise, performance and managing multiple clouds and its migration. Cloud computing models are discussed and its challenges are bifurcated into two broad categories technical and managerial aspects.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131855377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-01DOI: 10.1109/ICCS54944.2021.00023
J. Jyoti, Ranbir Singh Batth
With a rising industry, unmanned aerial vehicles (UAVs) provide a significant commercial opportunity for industries and numerous entrepreneurs as a means of replacing humans in dangerous missions and in hostile situations. The use of UAVs is rapidly growing in which energy-efficient path planning is a major issue. In this research article, a detailed classification of the entire path planning approaches for a UAV in terms of energy efficiency has been discussed, moreover, a detailed comparison between different path planning approaches is also provided. Multiple considerations are to be considered for an ideal path planning which includes path completeness, optimality. The execution of path planning becomes a challenging task in terms of trajectory generation and also requires careful consideration.
{"title":"Unmanned Aerial vehicles (UAV) Path Planning Approaches","authors":"J. Jyoti, Ranbir Singh Batth","doi":"10.1109/ICCS54944.2021.00023","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00023","url":null,"abstract":"With a rising industry, unmanned aerial vehicles (UAVs) provide a significant commercial opportunity for industries and numerous entrepreneurs as a means of replacing humans in dangerous missions and in hostile situations. The use of UAVs is rapidly growing in which energy-efficient path planning is a major issue. In this research article, a detailed classification of the entire path planning approaches for a UAV in terms of energy efficiency has been discussed, moreover, a detailed comparison between different path planning approaches is also provided. Multiple considerations are to be considered for an ideal path planning which includes path completeness, optimality. The execution of path planning becomes a challenging task in terms of trajectory generation and also requires careful consideration.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"216 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133823958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-01DOI: 10.1109/ICCS54944.2021.00062
Manu Prakram, Amanpreet Singh, Jagroop Singh
Restoration of an image with blocking artifacts caused by low-bit-rate compression is a difficult task, and blocking artifact assessment techniques play an essential role in the computer vision area. An artifacts removal approach is a critical step in improving the image processing area's dependability and security, allowing for improved understanding in a variety of applications such as pattern recognition, object categorization, surveillance systems. Removal of artifacts is a processing technique that is utilized to give improved picture Quality, and several artifacts removal procedures have previously been used by researchers in the image processing era for this goal. However, when a collection of artifacts is present in an image such as line artifacts, motion artifacts etc. they do not yield acceptable outcomes. We have suggested a comparative methodology for removing line and motion artifacts from digital images utilizing fuzzy logic in this study. This study's key contribution is the creation of a novel fuzzy logic-based hybrid artifacts removal system that improves blocking artifacts efficiency. The suggested framework has its own influence on quality parameters to remove artifact from a picture.
{"title":"A Comparative Framework for Blocking Artifacts Removal of compressed Images using Fuzzy Logic","authors":"Manu Prakram, Amanpreet Singh, Jagroop Singh","doi":"10.1109/ICCS54944.2021.00062","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00062","url":null,"abstract":"Restoration of an image with blocking artifacts caused by low-bit-rate compression is a difficult task, and blocking artifact assessment techniques play an essential role in the computer vision area. An artifacts removal approach is a critical step in improving the image processing area's dependability and security, allowing for improved understanding in a variety of applications such as pattern recognition, object categorization, surveillance systems. Removal of artifacts is a processing technique that is utilized to give improved picture Quality, and several artifacts removal procedures have previously been used by researchers in the image processing era for this goal. However, when a collection of artifacts is present in an image such as line artifacts, motion artifacts etc. they do not yield acceptable outcomes. We have suggested a comparative methodology for removing line and motion artifacts from digital images utilizing fuzzy logic in this study. This study's key contribution is the creation of a novel fuzzy logic-based hybrid artifacts removal system that improves blocking artifacts efficiency. The suggested framework has its own influence on quality parameters to remove artifact from a picture.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127913854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-01DOI: 10.1109/ICCS54944.2021.00068
Md. Mijanur Rahman, Tanjarul Islam Mishu
This paper concerns creating a fingerprint database named “FCJ2020 Fingerprint Dataset”, a part of the research project “Secure Template Generation Technique for Protecting Fingerprint Patterns from Security Attacks”. Generating fingerprint templates is an interesting issue in biometric authentication systems. The study aimed to create minutiae templates from the fingerprint images. The fingerprint image processing and feature extraction is an essential task in fingerprint recognition. This paper also presents the fingerprint image processing operations, feature extraction, and minutiae-based verification methods. The FCJ2020 database acquired 1200 fingerprints from fifty different persons. These fingerprint images were used to evaluate the performance of the proposed biometric authentication system.
{"title":"FCJ2020: Generating Fingerprint Templates with Image Processing and Verification","authors":"Md. Mijanur Rahman, Tanjarul Islam Mishu","doi":"10.1109/ICCS54944.2021.00068","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00068","url":null,"abstract":"This paper concerns creating a fingerprint database named “FCJ2020 Fingerprint Dataset”, a part of the research project “Secure Template Generation Technique for Protecting Fingerprint Patterns from Security Attacks”. Generating fingerprint templates is an interesting issue in biometric authentication systems. The study aimed to create minutiae templates from the fingerprint images. The fingerprint image processing and feature extraction is an essential task in fingerprint recognition. This paper also presents the fingerprint image processing operations, feature extraction, and minutiae-based verification methods. The FCJ2020 database acquired 1200 fingerprints from fifty different persons. These fingerprint images were used to evaluate the performance of the proposed biometric authentication system.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128338781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-01DOI: 10.1109/ICCS54944.2021.00021
Mohammad Umer, Shilpa Sharma, Punam Rattan
Deep learning algorithms have lately risen to prominence as the primary tool for processing medical images. These algorithms are suitable for solving these image processing problems because of their efficient learning abilities and the potential to deal with complex problems relatively easily. Deep Learning's usefulness in health domain has grown drastically over the past few years as the amount of medical data has expanded exponentially. The main deep learning models, that have become popular over a last few years, relevant to medical image analysis are reviewed in this work. Various studies based on medical image analysis using deep learning models are surveyed in this study. This study provides an overview of various technologies used in Deep Learning in medical imagery and gives a brief idea about their performance.
{"title":"A Survey of Deep Learning Models for Medical Image Analysis","authors":"Mohammad Umer, Shilpa Sharma, Punam Rattan","doi":"10.1109/ICCS54944.2021.00021","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00021","url":null,"abstract":"Deep learning algorithms have lately risen to prominence as the primary tool for processing medical images. These algorithms are suitable for solving these image processing problems because of their efficient learning abilities and the potential to deal with complex problems relatively easily. Deep Learning's usefulness in health domain has grown drastically over the past few years as the amount of medical data has expanded exponentially. The main deep learning models, that have become popular over a last few years, relevant to medical image analysis are reviewed in this work. Various studies based on medical image analysis using deep learning models are surveyed in this study. This study provides an overview of various technologies used in Deep Learning in medical imagery and gives a brief idea about their performance.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126344450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-01DOI: 10.1109/ICCS54944.2021.00044
Vikas Attri, I. Isha, A. Malik
Online reviews are one of the most important aspects in a buyer's choice to buy a new product or use a service. As a result, it serves as a helpful source of data for determining public opinion regarding these products and services. It also provides companies with an indication of what kind of changes they need to make in their products to improve further. Thus, reviews also give competitors and product-based organizations a possible option to create fake reviews in order to advertise or degrade a product based on their interest. Hence, it is vital that the correct reviews are reached to the customers, and for this, the detection of fake ones is to be done effectively. In order to reduce the time for fake review detection, automated techniques are being used in the current scenario. Another concern is how to differentiate between the original and fake reviews. This paper discusses the various factors that can help in the identification of the same. They are broadly classified into two types: behavioral and feature-based. Also, the challenges that are still there in fake the review identification methods are depicted, and the open research areas where further work can be carried out are also being highlighted. The factors mentioned in the paper can prove useful for improvising the performance of any fake review detection system once applied to any real data set.
{"title":"Parametric Analysis for Fake Reviews Identification","authors":"Vikas Attri, I. Isha, A. Malik","doi":"10.1109/ICCS54944.2021.00044","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00044","url":null,"abstract":"Online reviews are one of the most important aspects in a buyer's choice to buy a new product or use a service. As a result, it serves as a helpful source of data for determining public opinion regarding these products and services. It also provides companies with an indication of what kind of changes they need to make in their products to improve further. Thus, reviews also give competitors and product-based organizations a possible option to create fake reviews in order to advertise or degrade a product based on their interest. Hence, it is vital that the correct reviews are reached to the customers, and for this, the detection of fake ones is to be done effectively. In order to reduce the time for fake review detection, automated techniques are being used in the current scenario. Another concern is how to differentiate between the original and fake reviews. This paper discusses the various factors that can help in the identification of the same. They are broadly classified into two types: behavioral and feature-based. Also, the challenges that are still there in fake the review identification methods are depicted, and the open research areas where further work can be carried out are also being highlighted. The factors mentioned in the paper can prove useful for improvising the performance of any fake review detection system once applied to any real data set.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132658971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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