Several IoT applications have immediate impacts on daily lives. The notion of “connected life”, which includes IoT has been discussed. Apps that rely on localization are also featured. IoT is originally used to determine the precise position of things, animals, and people. The second tracks everyone and everything that's on the move, including pets, kids, and the elderly people. Localization and tracking are integral parts of security and surveillance systems in interconnected homes. This study reviews the state-of-the-art IoT-based localization and tracking approaches and outlines the key technical aspects, and contrast localization initiatives based on Internet of Things (IoT) with those that do not show how they might be used in a variety of contexts. It is now well established that localization and tracking methods based on the Internet of Things (IoT) are more pervasive and accurate than their predecessors.
{"title":"Tracking and Localization of Devices - An IoT Review","authors":"Sreeparnesh Sharma Sivadevuni, Sathish Kumar Ravichandran","doi":"10.1109/ICICT57646.2023.10134278","DOIUrl":"https://doi.org/10.1109/ICICT57646.2023.10134278","url":null,"abstract":"Several IoT applications have immediate impacts on daily lives. The notion of “connected life”, which includes IoT has been discussed. Apps that rely on localization are also featured. IoT is originally used to determine the precise position of things, animals, and people. The second tracks everyone and everything that's on the move, including pets, kids, and the elderly people. Localization and tracking are integral parts of security and surveillance systems in interconnected homes. This study reviews the state-of-the-art IoT-based localization and tracking approaches and outlines the key technical aspects, and contrast localization initiatives based on Internet of Things (IoT) with those that do not show how they might be used in a variety of contexts. It is now well established that localization and tracking methods based on the Internet of Things (IoT) are more pervasive and accurate than their predecessors.","PeriodicalId":126489,"journal":{"name":"2023 International Conference on Inventive Computation Technologies (ICICT)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121810016","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 : 2023-04-26DOI: 10.1109/ICICT57646.2023.10133975
Xiaolei Zhang, Xiaotao Zhang
This study has designed a path planning model for intelligent robot based on computer vision recognition algorithm. Here, the redundant nodes present in the pre-planned path are removed through the node screening mechanism, and the later the artificial potential field method is introduced to ensure that a safe distance is always maintained from the unknown obstacles present in the re-planning process. At the same time, this research study adopts the method of setting virtual target points to solve the local extreme value problem that may be encountered in the actual movement of the machine. For developing an efficient and intelligent path planning model, the computer vision should be referred. The binocular recognition is equipped with two symmetrical signal acquisition cameras, which can realize the positioning of the status information. The enhanced theoretical vision algorithm is then combined for performing systematic optimization. The performance is validated by testing it on different datasets.
{"title":"Path Planning Model of Intelligent Robot based on Computer Vision Recognition Algorithm","authors":"Xiaolei Zhang, Xiaotao Zhang","doi":"10.1109/ICICT57646.2023.10133975","DOIUrl":"https://doi.org/10.1109/ICICT57646.2023.10133975","url":null,"abstract":"This study has designed a path planning model for intelligent robot based on computer vision recognition algorithm. Here, the redundant nodes present in the pre-planned path are removed through the node screening mechanism, and the later the artificial potential field method is introduced to ensure that a safe distance is always maintained from the unknown obstacles present in the re-planning process. At the same time, this research study adopts the method of setting virtual target points to solve the local extreme value problem that may be encountered in the actual movement of the machine. For developing an efficient and intelligent path planning model, the computer vision should be referred. The binocular recognition is equipped with two symmetrical signal acquisition cameras, which can realize the positioning of the status information. The enhanced theoretical vision algorithm is then combined for performing systematic optimization. The performance is validated by testing it on different datasets.","PeriodicalId":126489,"journal":{"name":"2023 International Conference on Inventive Computation Technologies (ICICT)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115766153","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 : 2023-04-26DOI: 10.1109/ICICT57646.2023.10134398
Pranay Pandare, Sneha Uniyal, R. Vani, Shweta Mali, Priti Rumao
Password management is essential for keeping data safe and secure. With increasing threats from cyber criminals, it is essential to have secure and unique passwords for each online account. Password management software helps users to store passwords securely. Password management also helps users easily remember complex passwords and reduces the risk of their accounts being hacked. Additionally, password management can help organizations to manage and protect confidential data, ensuring that only authorized personnel have access to sensitive information. This paper presents a secure password management extension for web browsers. The extension is designed to provide users with an easy-to-use interface for securely storing and managing website passwords. It allows users to log into websites with a single click quickly and incorporates an advanced encryption algorithm to ensure data security and privacy. The extension is available for some major web browsers and is compatible with multiple operating systems. The extension is designed to be lightweight and efficient, using minimal system resources. Furthermore, the extension is regularly updated with the latest security protocols and updates, ensuring that users' passwords remain secure.
{"title":"Enhanced Password Manager using Hybrid Approach","authors":"Pranay Pandare, Sneha Uniyal, R. Vani, Shweta Mali, Priti Rumao","doi":"10.1109/ICICT57646.2023.10134398","DOIUrl":"https://doi.org/10.1109/ICICT57646.2023.10134398","url":null,"abstract":"Password management is essential for keeping data safe and secure. With increasing threats from cyber criminals, it is essential to have secure and unique passwords for each online account. Password management software helps users to store passwords securely. Password management also helps users easily remember complex passwords and reduces the risk of their accounts being hacked. Additionally, password management can help organizations to manage and protect confidential data, ensuring that only authorized personnel have access to sensitive information. This paper presents a secure password management extension for web browsers. The extension is designed to provide users with an easy-to-use interface for securely storing and managing website passwords. It allows users to log into websites with a single click quickly and incorporates an advanced encryption algorithm to ensure data security and privacy. The extension is available for some major web browsers and is compatible with multiple operating systems. The extension is designed to be lightweight and efficient, using minimal system resources. Furthermore, the extension is regularly updated with the latest security protocols and updates, ensuring that users' passwords remain secure.","PeriodicalId":126489,"journal":{"name":"2023 International Conference on Inventive Computation Technologies (ICICT)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127270613","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 : 2023-04-26DOI: 10.1109/ICICT57646.2023.10133976
Xingyu Ren
Efficiently implementing accurate human pose estimation is one of the most fundamental and challenging tasks in computer vision, then, the novel pose recognition algorithm based on multi-feature point fusion for the training images is proposed in this research work. This study considers 3-step framework to achieve the goal of efficient estimation. Step 1: non-maximum suppression of the gradient magnitude is considered in the improved Canny algorithm, the direction of the gradient can be defined as one of the four regions, and the edge information will be collected. Step 2: The Gabor feature and Haar feature are combined together to achieve the fused feature. Step 3: the convolutional neural network is used for pose recognition. y analyzing the bottom layer of the convolution operation, it can be seen that the convolution operation can only linearly transform the input and the efficient estimation result can be obtained. The proposed model is tested on the collected database, and the pose recognition performance is tested.
{"title":"A Novel Pose Recognition Algorithm based on Multi-Feature Point Fusion for Training Images","authors":"Xingyu Ren","doi":"10.1109/ICICT57646.2023.10133976","DOIUrl":"https://doi.org/10.1109/ICICT57646.2023.10133976","url":null,"abstract":"Efficiently implementing accurate human pose estimation is one of the most fundamental and challenging tasks in computer vision, then, the novel pose recognition algorithm based on multi-feature point fusion for the training images is proposed in this research work. This study considers 3-step framework to achieve the goal of efficient estimation. Step 1: non-maximum suppression of the gradient magnitude is considered in the improved Canny algorithm, the direction of the gradient can be defined as one of the four regions, and the edge information will be collected. Step 2: The Gabor feature and Haar feature are combined together to achieve the fused feature. Step 3: the convolutional neural network is used for pose recognition. y analyzing the bottom layer of the convolution operation, it can be seen that the convolution operation can only linearly transform the input and the efficient estimation result can be obtained. The proposed model is tested on the collected database, and the pose recognition performance is tested.","PeriodicalId":126489,"journal":{"name":"2023 International Conference on Inventive Computation Technologies (ICICT)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125294883","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 : 2023-04-26DOI: 10.1109/ICICT57646.2023.10134283
Harshitha Kolakaluru, T. Vishal, Medepalli Prem Chandu, Mamidala Harshini, T. Vignesh, Venkata Vara Prasad Padyala
Troublesome crop pests cause a significant loss of revenue for the agricultural sector of the economy. It is crucial for efficient pest control to have a prompt and precise identification of both the pests themselves as well as the harm that cause. This essay will not only explain why it is so crucial to identify agricultural pests correctly, but it will also discuss the steps to attain that exact goal. When weeds and other agricultural pests are accurately recognized, it is much simpler to eradicate them using a management strategy that follows a systematic approach. It is essential for accurate pest identification, predicting how the pest will behave, and eradicating the pest. These data are essential for making sound decisions on IPM practices and applying pesticides effectively.
{"title":"Crop Disease Identification using Convolutional Neural Network","authors":"Harshitha Kolakaluru, T. Vishal, Medepalli Prem Chandu, Mamidala Harshini, T. Vignesh, Venkata Vara Prasad Padyala","doi":"10.1109/ICICT57646.2023.10134283","DOIUrl":"https://doi.org/10.1109/ICICT57646.2023.10134283","url":null,"abstract":"Troublesome crop pests cause a significant loss of revenue for the agricultural sector of the economy. It is crucial for efficient pest control to have a prompt and precise identification of both the pests themselves as well as the harm that cause. This essay will not only explain why it is so crucial to identify agricultural pests correctly, but it will also discuss the steps to attain that exact goal. When weeds and other agricultural pests are accurately recognized, it is much simpler to eradicate them using a management strategy that follows a systematic approach. It is essential for accurate pest identification, predicting how the pest will behave, and eradicating the pest. These data are essential for making sound decisions on IPM practices and applying pesticides effectively.","PeriodicalId":126489,"journal":{"name":"2023 International Conference on Inventive Computation Technologies (ICICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115551938","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 : 2023-04-26DOI: 10.1109/ICICT57646.2023.10134480
Darshanaben D. Pandya, Amit Patel, Janki Manishkumar Purohit, Madhavi Nandlal Bhuptani, S. Degadwala, Dhairya Vyas
For regulators and investors, estimating the potential of the Indian market requires accurately predicting the number of startups in the Indian ecosystem. Startup growth may be predicted with great accuracy using Supervised Learning Regression models. These models take into account a wide range of variables, including financing, market demand, and competition. The purpose of this research is to use Supervised Learning Regression models to make predictions about the future of the startup scene in India. Information from the Startup Database, official papers, and scholarly journals all factored into the analysis. Supervised Learning Regression models are then used to make predictions about future growth based on the identified variables, using training data taken from the past. Factors including finance availability, government regulations, and market demand are identified in the report as having a substantial influence on the number of startups in India. The potential expansion of the startup sector in India is foreseen by using Supervised Learning Regression models to forecast the future number of companies in the Indian ecosystem. The findings of this research support the use of linear models for estimating future startup activity in India. Policymakers and investors may benefit from this study's results by learning more about the forces that are propelling India's startup scene forward.
{"title":"Forecasting Number of Indian Startups using Supervised Learning Regression Models","authors":"Darshanaben D. Pandya, Amit Patel, Janki Manishkumar Purohit, Madhavi Nandlal Bhuptani, S. Degadwala, Dhairya Vyas","doi":"10.1109/ICICT57646.2023.10134480","DOIUrl":"https://doi.org/10.1109/ICICT57646.2023.10134480","url":null,"abstract":"For regulators and investors, estimating the potential of the Indian market requires accurately predicting the number of startups in the Indian ecosystem. Startup growth may be predicted with great accuracy using Supervised Learning Regression models. These models take into account a wide range of variables, including financing, market demand, and competition. The purpose of this research is to use Supervised Learning Regression models to make predictions about the future of the startup scene in India. Information from the Startup Database, official papers, and scholarly journals all factored into the analysis. Supervised Learning Regression models are then used to make predictions about future growth based on the identified variables, using training data taken from the past. Factors including finance availability, government regulations, and market demand are identified in the report as having a substantial influence on the number of startups in India. The potential expansion of the startup sector in India is foreseen by using Supervised Learning Regression models to forecast the future number of companies in the Indian ecosystem. The findings of this research support the use of linear models for estimating future startup activity in India. Policymakers and investors may benefit from this study's results by learning more about the forces that are propelling India's startup scene forward.","PeriodicalId":126489,"journal":{"name":"2023 International Conference on Inventive Computation Technologies (ICICT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122545556","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 : 2023-04-26DOI: 10.1109/ICICT57646.2023.10134239
Boomika S, K. M., A. M, Munusamy S
The most prevalent condition in the world is Tension-Type Headache (TTH). The impact of the illness was investigated using biofeedback (BF) and electromyography (EMG) to determine the person's headache. There has been any audio, visual, combined EMG or GSR BF analysis in TTH, though. In order to do this, the proposed study will test the effectiveness of galvanic skin resistance and electromyography biofeedback in TTH patients as well as analyze and assess the effectiveness of patients' audio, perception, and audio-perception. Out of 240 respondents in a particular dataset, 140 are female and the remaining 100 are male. Currently, seven groups were randomly allocated, including a control group (n = 26), electromyography feedback auditory (EMGa) (n = 28), visual (EMGv) (n = 27), combination audio-visual (EMGav) (n = 28), and galvanic skin resistance biofeedback auditory (GSRa) (n = 28). While every individual has 15 separate 30-minute biofeedback procedures in a quiet environment, EMG and GSR biofeedback are effective tools for examining TTH too.
{"title":"Stress Measurement and Analysis of Galvanic Skin Resistance (GSR) using EMG Signal","authors":"Boomika S, K. M., A. M, Munusamy S","doi":"10.1109/ICICT57646.2023.10134239","DOIUrl":"https://doi.org/10.1109/ICICT57646.2023.10134239","url":null,"abstract":"The most prevalent condition in the world is Tension-Type Headache (TTH). The impact of the illness was investigated using biofeedback (BF) and electromyography (EMG) to determine the person's headache. There has been any audio, visual, combined EMG or GSR BF analysis in TTH, though. In order to do this, the proposed study will test the effectiveness of galvanic skin resistance and electromyography biofeedback in TTH patients as well as analyze and assess the effectiveness of patients' audio, perception, and audio-perception. Out of 240 respondents in a particular dataset, 140 are female and the remaining 100 are male. Currently, seven groups were randomly allocated, including a control group (n = 26), electromyography feedback auditory (EMGa) (n = 28), visual (EMGv) (n = 27), combination audio-visual (EMGav) (n = 28), and galvanic skin resistance biofeedback auditory (GSRa) (n = 28). While every individual has 15 separate 30-minute biofeedback procedures in a quiet environment, EMG and GSR biofeedback are effective tools for examining TTH too.","PeriodicalId":126489,"journal":{"name":"2023 International Conference on Inventive Computation Technologies (ICICT)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117016809","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}
Because of metastasis, which spreads breast cancer from one region of the body to another through the lymphatic system and bloodstream, breast cancer has become a severe issue for women, and early detection of metastasis in breast cancer patients is essential to lowering the death rate of female patients. The challenges faced by transfer learning are Choosing the Right Pre-Trained Model, Overfitting, and bias. Subsequently, utilizing histopathological images, a stacking ensemble approach is used by considering the pre-trained deep convolutional neural networks VGG-19, InceptionResNetV2, and the newly designed architecture called the Baseline model. These models were trained separately on the dataset before being integrated using the stacking ensemble technique. Among the pre-trained models, the baseline model got better accuracy. When these three models are combined using a stacking ensemble the ensembled model obtained better results than individual pre-trained models.
{"title":"Detection of Metastasis in Breast Cancer Patients using Deep Neural Networks by Ensemble Stacking","authors":"Surendra Reddy Sanayapalli, Sunitha Munappa, Leela Priyanka Mirtipati, Lakshmi Narayana Srirama, Sri Lakshmi Vuyyala","doi":"10.1109/ICICT57646.2023.10134435","DOIUrl":"https://doi.org/10.1109/ICICT57646.2023.10134435","url":null,"abstract":"Because of metastasis, which spreads breast cancer from one region of the body to another through the lymphatic system and bloodstream, breast cancer has become a severe issue for women, and early detection of metastasis in breast cancer patients is essential to lowering the death rate of female patients. The challenges faced by transfer learning are Choosing the Right Pre-Trained Model, Overfitting, and bias. Subsequently, utilizing histopathological images, a stacking ensemble approach is used by considering the pre-trained deep convolutional neural networks VGG-19, InceptionResNetV2, and the newly designed architecture called the Baseline model. These models were trained separately on the dataset before being integrated using the stacking ensemble technique. Among the pre-trained models, the baseline model got better accuracy. When these three models are combined using a stacking ensemble the ensembled model obtained better results than individual pre-trained models.","PeriodicalId":126489,"journal":{"name":"2023 International Conference on Inventive Computation Technologies (ICICT)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128792850","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 : 2023-04-26DOI: 10.1109/ICICT57646.2023.10133959
M. Navaneethakrishnan, R. Kalaiyarasi, T. A. Mohanaprakash, B. Bala Abirami, A. S. Prakaash, V. Malathi
This research study proposes an Artificial Intelligence based women security and safety system to provide a safe and secure platform to discuss about the problems faced by the women in today's society and provide a better solution for it. The proposed application helps them to open up their mind, as they see so many girls of their age and also the elderly women sharing their problems. This software is mainly developed for Indian citizens and it is jointly operating with the police of different regions of India and psychiatrist with the intention of developing a crime free nation, where women can live independently.
{"title":"(WoExP)Women Express-Artificial Intelligence based women security and Safety System","authors":"M. Navaneethakrishnan, R. Kalaiyarasi, T. A. Mohanaprakash, B. Bala Abirami, A. S. Prakaash, V. Malathi","doi":"10.1109/ICICT57646.2023.10133959","DOIUrl":"https://doi.org/10.1109/ICICT57646.2023.10133959","url":null,"abstract":"This research study proposes an Artificial Intelligence based women security and safety system to provide a safe and secure platform to discuss about the problems faced by the women in today's society and provide a better solution for it. The proposed application helps them to open up their mind, as they see so many girls of their age and also the elderly women sharing their problems. This software is mainly developed for Indian citizens and it is jointly operating with the police of different regions of India and psychiatrist with the intention of developing a crime free nation, where women can live independently.","PeriodicalId":126489,"journal":{"name":"2023 International Conference on Inventive Computation Technologies (ICICT)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128296001","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 : 2023-04-26DOI: 10.1109/ICICT57646.2023.10134213
Kallam Vedaswi, N. Krishna, Tanguturi Vyshnavi Poojitha, Pantangi Lokesh, K. Ashesh, Priyesh Kumar
A recommendation system searches for content that would be Interesting to a specific person. Its goal is to build customer trust by offering content that is relevant which will increase the time spent of a digital platform. Additionally, this will also enhance user experience. The main objective of this strategy is to combine a content-based and collaborative approach. The proposed system can recommend a variety of movies to customers based on their interests or the box office performance of the movies. Collaborative filtering seeks to consider user opinions of various videos in order to suggest the best video to each user based on their past rankings and the views of other users, who share similar interests.
{"title":"Movie Recommendation using Collaborative filtering and Content-based Filtering Approach","authors":"Kallam Vedaswi, N. Krishna, Tanguturi Vyshnavi Poojitha, Pantangi Lokesh, K. Ashesh, Priyesh Kumar","doi":"10.1109/ICICT57646.2023.10134213","DOIUrl":"https://doi.org/10.1109/ICICT57646.2023.10134213","url":null,"abstract":"A recommendation system searches for content that would be Interesting to a specific person. Its goal is to build customer trust by offering content that is relevant which will increase the time spent of a digital platform. Additionally, this will also enhance user experience. The main objective of this strategy is to combine a content-based and collaborative approach. The proposed system can recommend a variety of movies to customers based on their interests or the box office performance of the movies. Collaborative filtering seeks to consider user opinions of various videos in order to suggest the best video to each user based on their past rankings and the views of other users, who share similar interests.","PeriodicalId":126489,"journal":{"name":"2023 International Conference on Inventive Computation Technologies (ICICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128606192","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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