Pub Date : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987388
B. Saravanan, M. Duraipandian, V. Pandiaraj
The segmentation of tumors in magnetic resonance imaging (MRI) is a medical emergency operation. Weakened MR images of the brain are used to segment them using the fuzzy C-means (FCM) clustering technique. The run time is longer because of the need to continuously calculate the clustering parameters. Using the probabilistic fuzzy clustering (PFC) technique for brain MRI image segmentation is recommended by the authors of this article. Morphological reconstruction and computation of local spatial similarity factors are performed before commencing the clustering step. Integrating a local spatial similarity factor into the morphological reconstruction process reduces noise, while maintaining the information's structural integrity.
{"title":"An Effective Possibilistic Fuzzy Clustering Method for Tumor Segmentation in MRI brain Images","authors":"B. Saravanan, M. Duraipandian, V. Pandiaraj","doi":"10.1109/I-SMAC55078.2022.9987388","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987388","url":null,"abstract":"The segmentation of tumors in magnetic resonance imaging (MRI) is a medical emergency operation. Weakened MR images of the brain are used to segment them using the fuzzy C-means (FCM) clustering technique. The run time is longer because of the need to continuously calculate the clustering parameters. Using the probabilistic fuzzy clustering (PFC) technique for brain MRI image segmentation is recommended by the authors of this article. Morphological reconstruction and computation of local spatial similarity factors are performed before commencing the clustering step. Integrating a local spatial similarity factor into the morphological reconstruction process reduces noise, while maintaining the information's structural integrity.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133712454","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987249
R. Vaibhava Lakshmi, G. Deepak, A. Santhanavijayan, S. Radha
An emerging constituent of Internet of Things is the Social IoT, which aids creation of Social relationships amongst interacting objects. SIoT attempts to moderate the shortcomings of IoT in the areas of trust, resource discovery and scalability by taking a cue from social computing. In this paper, we have proposed the OntoSSSO framework for recommending Socially Similar Smart objects to users, which is knowledge-centric, ontology-driven and dataset-driven. It incorporates Semantic Intelligence. The proffered model is compared for performance along with the baseline models using sundry performance metrics. Our model outperforms the other models, yielding a precision of 95.83 %.
{"title":"Search for Social Smart Objects Constituting Sensor Ontology, Social IoT and Social Network Interaction","authors":"R. Vaibhava Lakshmi, G. Deepak, A. Santhanavijayan, S. Radha","doi":"10.1109/I-SMAC55078.2022.9987249","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987249","url":null,"abstract":"An emerging constituent of Internet of Things is the Social IoT, which aids creation of Social relationships amongst interacting objects. SIoT attempts to moderate the shortcomings of IoT in the areas of trust, resource discovery and scalability by taking a cue from social computing. In this paper, we have proposed the OntoSSSO framework for recommending Socially Similar Smart objects to users, which is knowledge-centric, ontology-driven and dataset-driven. It incorporates Semantic Intelligence. The proffered model is compared for performance along with the baseline models using sundry performance metrics. Our model outperforms the other models, yielding a precision of 95.83 %.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132843418","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987307
Lee Yi Yong, S. Gobee, V. Durairajah
Human-Robot Interaction (HRI) can improve a system effectiveness if implemented properly. This project presents an HRI interactive system to control a humanoid robot using vision and voice. The proposed system is aimed to ease the difficulty of controlling a robot as well as create an effective vision and voice system. The vision system is implemented in the form of a color-based object tracking system on the robot head while the voice-controlled system is implemented in the form of limb movement control through voice commands. As a result, they achieve an average accuracy of 84% and 84.29% respectively. The robot head and limb movement also achieve a maximum average error of 2° and 2.11° only. Finally, the voice-controlled system has an average response time of 1.73s. Possible future enhancements include considering other feature in the object tracking system such as texture and noise filtering on the voice recognition to improve their accuracy.
{"title":"An Interactive System to Control a Humanoid Robot using Vision and Voice","authors":"Lee Yi Yong, S. Gobee, V. Durairajah","doi":"10.1109/I-SMAC55078.2022.9987307","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987307","url":null,"abstract":"Human-Robot Interaction (HRI) can improve a system effectiveness if implemented properly. This project presents an HRI interactive system to control a humanoid robot using vision and voice. The proposed system is aimed to ease the difficulty of controlling a robot as well as create an effective vision and voice system. The vision system is implemented in the form of a color-based object tracking system on the robot head while the voice-controlled system is implemented in the form of limb movement control through voice commands. As a result, they achieve an average accuracy of 84% and 84.29% respectively. The robot head and limb movement also achieve a maximum average error of 2° and 2.11° only. Finally, the voice-controlled system has an average response time of 1.73s. Possible future enhancements include considering other feature in the object tracking system such as texture and noise filtering on the voice recognition to improve their accuracy.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133317996","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987276
G. Sajiv, G. Ramkumar
Cancer is a significant public health problem that is experienced by people all around the world. This disease has already taken the lives of a significant number of people, and it will continue to do so in the years to come. Breast cancer has already surpassed cervical cancer as the largest frequent form of cancer detected in females in both developed and developing countries, making it the second leading cause of cancer death among women worldwide. This disease claims the lives of a significant number of women each and every year. If detected at an earlier stage, breast cancer is substantially easier to treat. In this study, a decision tree-based categorization of breast cancer in histological images is presented for the first time. Both benign and malignant breast growths can eventually develop into breast cancers. Researchers use classification as a tool to assess and classify the medical data they collect. Segmentation is a key factor in the identification of breast cancer. In order to train the model, the cancer specimens that can be found in the Kaggle archive are employed. The classification used by Decision Tree has an overall accuracy of 87.28 percent. These results provide evidence to support the utilization of the suggested machine learning-based Decision Tree classifier in the pre-evaluation of patients for the purposes of triage and decision-making prior to the provision of data.
{"title":"Machine Learning based Analysis of Histopathological Images of Breast Cancer Classification using Decision Tree Classifier","authors":"G. Sajiv, G. Ramkumar","doi":"10.1109/I-SMAC55078.2022.9987276","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987276","url":null,"abstract":"Cancer is a significant public health problem that is experienced by people all around the world. This disease has already taken the lives of a significant number of people, and it will continue to do so in the years to come. Breast cancer has already surpassed cervical cancer as the largest frequent form of cancer detected in females in both developed and developing countries, making it the second leading cause of cancer death among women worldwide. This disease claims the lives of a significant number of women each and every year. If detected at an earlier stage, breast cancer is substantially easier to treat. In this study, a decision tree-based categorization of breast cancer in histological images is presented for the first time. Both benign and malignant breast growths can eventually develop into breast cancers. Researchers use classification as a tool to assess and classify the medical data they collect. Segmentation is a key factor in the identification of breast cancer. In order to train the model, the cancer specimens that can be found in the Kaggle archive are employed. The classification used by Decision Tree has an overall accuracy of 87.28 percent. These results provide evidence to support the utilization of the suggested machine learning-based Decision Tree classifier in the pre-evaluation of patients for the purposes of triage and decision-making prior to the provision of data.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130527357","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987427
K. Chande, Rahul Kanekar, Kiran Nair, Dina Amandykova, Supriya Addanke, Tolegen Zhaina
At present, green communication technology is receiving a significant research attention. The increasing research interest on green communication can also undermine the environment. Measuring the green communication intensity of various products, companies and processes is being carried out globally by following the rule that only the related effects are manageable, which is expressed as a carbon footprint. Green detections are having a direct, large-scale impact on carbon productions. The green initiatives can effectively reduce carbon productions by improving the energy efficiency. In summary, green discovery directly affect carbon production. This research work has attempted to reduce the carbon footprint energy by using Enhanced Recurrent Neural Network (ERNN). From an investment perspective, carbon footprint analysis can assist in evaluating a company’s overall and comparative performance. It can be used as a tool to manage and evaluate the performance of a company. Effective production management demonstrates the quality of operations and can provide a significant competitive advantage.
{"title":"Enhanced Recurrent Neural Network for Reducing Carbon Foot Printing in Industry","authors":"K. Chande, Rahul Kanekar, Kiran Nair, Dina Amandykova, Supriya Addanke, Tolegen Zhaina","doi":"10.1109/I-SMAC55078.2022.9987427","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987427","url":null,"abstract":"At present, green communication technology is receiving a significant research attention. The increasing research interest on green communication can also undermine the environment. Measuring the green communication intensity of various products, companies and processes is being carried out globally by following the rule that only the related effects are manageable, which is expressed as a carbon footprint. Green detections are having a direct, large-scale impact on carbon productions. The green initiatives can effectively reduce carbon productions by improving the energy efficiency. In summary, green discovery directly affect carbon production. This research work has attempted to reduce the carbon footprint energy by using Enhanced Recurrent Neural Network (ERNN). From an investment perspective, carbon footprint analysis can assist in evaluating a company’s overall and comparative performance. It can be used as a tool to manage and evaluate the performance of a company. Effective production management demonstrates the quality of operations and can provide a significant competitive advantage.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127161347","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987278
Rajesh P Sukumaran, S. Benedict
The rapid emergence of Internet of Things (IoT) has fueled the wide acceptance of its own extended version Industrial IoT(IIoT). It provides a real-time, robust, and reliable communication in various domains, including robotics, medical sensors, and other software-defined applications. In general, authentication is considered as the prime security control in IIoT systems to ensure that a right user is accessing resources at any specified time. Many research works have been presented in the literature so far with regard to improving the authentication and security aspects of industrial IIoT systems. This paper aims at presenting a comprehensive study on security and authentication aspects in IIoT systems; it highlights the existing cryptographic methods for such IIoT systems. Further, some of the existing research works on the IIoT systems, along with their strengths and weaknesses, are also been reviewed and presented. The work will be useful for researchers or practitioners while applying authentication techniques on IIoT systems.
{"title":"Authentication and Cryptography solutions for Industrial IoT - A Study","authors":"Rajesh P Sukumaran, S. Benedict","doi":"10.1109/I-SMAC55078.2022.9987278","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987278","url":null,"abstract":"The rapid emergence of Internet of Things (IoT) has fueled the wide acceptance of its own extended version Industrial IoT(IIoT). It provides a real-time, robust, and reliable communication in various domains, including robotics, medical sensors, and other software-defined applications. In general, authentication is considered as the prime security control in IIoT systems to ensure that a right user is accessing resources at any specified time. Many research works have been presented in the literature so far with regard to improving the authentication and security aspects of industrial IIoT systems. This paper aims at presenting a comprehensive study on security and authentication aspects in IIoT systems; it highlights the existing cryptographic methods for such IIoT systems. Further, some of the existing research works on the IIoT systems, along with their strengths and weaknesses, are also been reviewed and presented. The work will be useful for researchers or practitioners while applying authentication techniques on IIoT systems.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130036429","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987365
Nongmeikapam Thoiba Singh, R. Lal, Amrita Chaudhary, Simarjeet Kaur
Mobile ad hoc networks collect wireless technology that enhances the ad hoc network in various situations, such as difficult releases, critical consultation or military duty, and even a lack of network infrastructure maintenance. Due to the fact that nodes can join or leave the network at your discretion, the network's topology may vary often. Nodes synchronize in mobile ad hoc networks to keep in touch with one another. Data is transferred from the source to the destination via central nodes. A node has dual functionality-host and router. This article outlines the most efficient method for moving nodes efficiently between sources and destinations while lowering computing costs and raising acquisition precision. Researchers use machine learning to solve issues with temporary networks and different mobile ad hoc network agreements in this study and the conversation. Many machine learning techniques that are used in wireless ad hoc networks are described, along with how they extract the most important criteria, restore them, and identify where they are. The most significant recent and continuing research in this area is also summarized in this paper.
{"title":"A Review Paper on the Application of Machine Learning for Ad-Hoc Network","authors":"Nongmeikapam Thoiba Singh, R. Lal, Amrita Chaudhary, Simarjeet Kaur","doi":"10.1109/I-SMAC55078.2022.9987365","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987365","url":null,"abstract":"Mobile ad hoc networks collect wireless technology that enhances the ad hoc network in various situations, such as difficult releases, critical consultation or military duty, and even a lack of network infrastructure maintenance. Due to the fact that nodes can join or leave the network at your discretion, the network's topology may vary often. Nodes synchronize in mobile ad hoc networks to keep in touch with one another. Data is transferred from the source to the destination via central nodes. A node has dual functionality-host and router. This article outlines the most efficient method for moving nodes efficiently between sources and destinations while lowering computing costs and raising acquisition precision. Researchers use machine learning to solve issues with temporary networks and different mobile ad hoc network agreements in this study and the conversation. Many machine learning techniques that are used in wireless ad hoc networks are described, along with how they extract the most important criteria, restore them, and identify where they are. The most significant recent and continuing research in this area is also summarized in this paper.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129429111","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987337
Fushan Ma, Chunhui Shao
This paper mainly uses the genetic algorithm to further improve the facial recognition algorithm of the principal component analysis, and uses the genetic algorithm to optimize the selection of the feature space of the facial recognition algorithm of the principal component analysis. The first is to improve the coding bit number of the genetic algorithm. N bits. This paper adopts the methods of combining empirical analysis and case analysis, combining theory and practice, and taking Shandong Jinding Zhida as an example to analyze the existence of human resources performance management system in the current management process of small and medium-sized enterprises in my country. The main problem evaluation system and corporate strategy. The career integration degree of employees is not high, which restricts the healthy development of human resources of small and medium-sized enterprises.
{"title":"Informatization of Human Resources Performance Management in SMSE Based on Intelligent Analysis Algorithm","authors":"Fushan Ma, Chunhui Shao","doi":"10.1109/I-SMAC55078.2022.9987337","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987337","url":null,"abstract":"This paper mainly uses the genetic algorithm to further improve the facial recognition algorithm of the principal component analysis, and uses the genetic algorithm to optimize the selection of the feature space of the facial recognition algorithm of the principal component analysis. The first is to improve the coding bit number of the genetic algorithm. N bits. This paper adopts the methods of combining empirical analysis and case analysis, combining theory and practice, and taking Shandong Jinding Zhida as an example to analyze the existence of human resources performance management system in the current management process of small and medium-sized enterprises in my country. The main problem evaluation system and corporate strategy. The career integration degree of employees is not high, which restricts the healthy development of human resources of small and medium-sized enterprises.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129218884","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987288
Yi Wang
Based on the multi-agent technology, based on the characteristics of the existing cyclic data analysis calculation model, combined with the functional requirements of the distributed information acquisition system, this paper constructs the formal architecture MMFA of the multi-computing model integration distributed information acquisition system. Researched the technology related to data communication and applied it in engineering. In this research, the research on data communication technology mainly focuses on the serial communication between the CP machine and the lower computer (SCM). Discussed the possibility of using multi-agent and other technologies for modeling, and established a formal abstract architecture based on the fusion of multiple computing modes.
{"title":"Research Development of Computer Information Acquisition System based on Cyclic Data Analysis","authors":"Yi Wang","doi":"10.1109/I-SMAC55078.2022.9987288","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987288","url":null,"abstract":"Based on the multi-agent technology, based on the characteristics of the existing cyclic data analysis calculation model, combined with the functional requirements of the distributed information acquisition system, this paper constructs the formal architecture MMFA of the multi-computing model integration distributed information acquisition system. Researched the technology related to data communication and applied it in engineering. In this research, the research on data communication technology mainly focuses on the serial communication between the CP machine and the lower computer (SCM). Discussed the possibility of using multi-agent and other technologies for modeling, and established a formal abstract architecture based on the fusion of multiple computing modes.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129234420","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987258
Jun Chen
This paper studies the accuracy and rationality of machine English translation based on the LBP algorithm, and proposes a machine English translation method based on the selection of the optimal solution of fuzzy semantics. Construct an information extraction model for machine English translation, establish a fuzzy semantic topic word attribute table for machine English translation, and use phrases as the basic granularity to produce paraphrase results that are semantically consistent with the translation hypothesis set. Extract phrase paraphrase resources by using massively parallel corpus. Experimental test results show that using this method for machine English translation improves the recall performance of semantic information by 6.7%, and the feature matching degree of topic words is higher.
{"title":"Selection Method of Fuzzy Semantics in Machine Translation and the Integration of LBP Algorithm","authors":"Jun Chen","doi":"10.1109/I-SMAC55078.2022.9987258","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987258","url":null,"abstract":"This paper studies the accuracy and rationality of machine English translation based on the LBP algorithm, and proposes a machine English translation method based on the selection of the optimal solution of fuzzy semantics. Construct an information extraction model for machine English translation, establish a fuzzy semantic topic word attribute table for machine English translation, and use phrases as the basic granularity to produce paraphrase results that are semantically consistent with the translation hypothesis set. Extract phrase paraphrase resources by using massively parallel corpus. Experimental test results show that using this method for machine English translation improves the recall performance of semantic information by 6.7%, and the feature matching degree of topic words is higher.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121169003","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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