Pub Date : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9753806
Baixiang Fan, Bo Yin, Xuezhen Chen
This article comprehensively uses the Internet of Things technology, uses various Internet of Things devices to determine the real-time status of the power container to determine the parameter extraction process, and establish a power easy intelligent security system based on the Internet of Things technology, comprehensively using the Internet of Things radio frequency identification and sensor technology. Realize the intelligent monitoring, warning and temperature adjustment of the operating environment of the box substation. This system is mainly composed of remote control system, STM32 real-time control system, data collection system and data processing system, and fuzzy adaptive PID control system. The remote control system is mainly for remote monitoring and remote control; the STM32 control system is mainly responsible for coordinating the data collection system and the data processing system, and communicates with the remote control system through the network.
{"title":"Application Strategies in the Safety Management of Power Containers under the Power Smart Internet of Things","authors":"Baixiang Fan, Bo Yin, Xuezhen Chen","doi":"10.1109/ICCMC53470.2022.9753806","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753806","url":null,"abstract":"This article comprehensively uses the Internet of Things technology, uses various Internet of Things devices to determine the real-time status of the power container to determine the parameter extraction process, and establish a power easy intelligent security system based on the Internet of Things technology, comprehensively using the Internet of Things radio frequency identification and sensor technology. Realize the intelligent monitoring, warning and temperature adjustment of the operating environment of the box substation. This system is mainly composed of remote control system, STM32 real-time control system, data collection system and data processing system, and fuzzy adaptive PID control system. The remote control system is mainly for remote monitoring and remote control; the STM32 control system is mainly responsible for coordinating the data collection system and the data processing system, and communicates with the remote control system through the network.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"2012 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121327528","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 : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9753739
N. Kanagavalli, S. Priya, J. D
Recently, social networks have become more popular owing to the capability of connecting people globally and sharing videos, images and various types of data. A major security issue in social media is the existence of fake accounts. It is a phenomenon that has fake accounts that can be frequently utilized by mischievous users and entities, which falsify, distribute, and duplicate fake news and publicity. As the fake news resulted in serious consequences, numerous research works have focused on the design of automated fake accounts and fake news detection models. In this aspect, this study designs a hyperparameter tuned deep learning based automated fake news detection (HDL-FND) technique. The presented HDL-FND technique accomplishes the effective detection and classification of fake news. Besides, the HDLFND process encompasses a three stage process namely preprocessing, feature extraction, and Bi-Directional Long Short Term Memory (BiLSTM) based classification. The correct way of demonstrating the promising performance of the HDL-FND technique, a sequence of replications were performed on the available Kaggle dataset. The investigational outcomes produce improved performance of the HDL-FND technique in excess of the recent approaches in terms of diverse measures.
{"title":"Design of Hyperparameter Tuned Deep Learning based Automated Fake News Detection in Social Networking Data","authors":"N. Kanagavalli, S. Priya, J. D","doi":"10.1109/ICCMC53470.2022.9753739","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753739","url":null,"abstract":"Recently, social networks have become more popular owing to the capability of connecting people globally and sharing videos, images and various types of data. A major security issue in social media is the existence of fake accounts. It is a phenomenon that has fake accounts that can be frequently utilized by mischievous users and entities, which falsify, distribute, and duplicate fake news and publicity. As the fake news resulted in serious consequences, numerous research works have focused on the design of automated fake accounts and fake news detection models. In this aspect, this study designs a hyperparameter tuned deep learning based automated fake news detection (HDL-FND) technique. The presented HDL-FND technique accomplishes the effective detection and classification of fake news. Besides, the HDLFND process encompasses a three stage process namely preprocessing, feature extraction, and Bi-Directional Long Short Term Memory (BiLSTM) based classification. The correct way of demonstrating the promising performance of the HDL-FND technique, a sequence of replications were performed on the available Kaggle dataset. The investigational outcomes produce improved performance of the HDL-FND technique in excess of the recent approaches in terms of diverse measures.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"446 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125772203","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 : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9753751
Siddhartha Mohammad, Tapesh Bhowmick, Md. Shovon Uz Zaman Siddique, Mohammad Monirujjaman Khan, Sumanta Bhattacharyya
The fundamental reason for the venture "AI-Based Smart Medical Box '' is to propose the essential thought of programmed medication update, which will help patients take their recommended medication suitably with appropriate dosages. It is a clever plan to help the patient take as much time as is needed and, thus, lessen an opportunity to recuperate from their infection. Specifically, the matured patient takes some unacceptable medication and some unacceptable measurements mistakenly, causing a serious issue. This framework isn't only useful for an individual but can likewise make a significant commitment to medical clinics. In the present occupied, pushed, and booked life, individuals are experiencing loads of illnesses but can't recall their medication and timing of it, and here this framework can be of genuine use. This framework utilizes an LCD (fluid precious stone showcase), keypad (press button), ARDUINO module, RTC framework, and an alert framework. As per the odder gadgets, this smart medicine box is planned in light of a lower cost. Thus, this convenient and monetarily cheaper framework would be useful to each age group.
{"title":"Research and Development of a Artificial Intelligence based Smart Medicine Box","authors":"Siddhartha Mohammad, Tapesh Bhowmick, Md. Shovon Uz Zaman Siddique, Mohammad Monirujjaman Khan, Sumanta Bhattacharyya","doi":"10.1109/ICCMC53470.2022.9753751","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753751","url":null,"abstract":"The fundamental reason for the venture \"AI-Based Smart Medical Box '' is to propose the essential thought of programmed medication update, which will help patients take their recommended medication suitably with appropriate dosages. It is a clever plan to help the patient take as much time as is needed and, thus, lessen an opportunity to recuperate from their infection. Specifically, the matured patient takes some unacceptable medication and some unacceptable measurements mistakenly, causing a serious issue. This framework isn't only useful for an individual but can likewise make a significant commitment to medical clinics. In the present occupied, pushed, and booked life, individuals are experiencing loads of illnesses but can't recall their medication and timing of it, and here this framework can be of genuine use. This framework utilizes an LCD (fluid precious stone showcase), keypad (press button), ARDUINO module, RTC framework, and an alert framework. As per the odder gadgets, this smart medicine box is planned in light of a lower cost. Thus, this convenient and monetarily cheaper framework would be useful to each age group.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125871506","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 : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9753843
Nageswara Rao Atyam, Ramesh Babu P, P. Ponmurugan, L. Senthamil, P. John Augustine, A. Govindarajan
In recent era, the supply chain management is becoming a complex valued network that offers a major competitive advantage over logistics and supply chain management. Despite its advantages, the complexity is becoming a challenge that should provide verification of sources, maintaining product visibility and monitoring while moving via supply chains. The adoption of Internet of Things (IoT) can support all these movements that tends to track and monitor the activities of the products moving in the chain network. Such optimization enables the operations to get optimized that includes manufacturing, warehousing and transportation. In addition, the transparency of the supply chains can be maintained via blockchain and when combined with IoT, it increases the effectiveness and efficacy of the supply chain
{"title":"Integrated Internet of Things with Blockchains for Vendor-Management Inventory System","authors":"Nageswara Rao Atyam, Ramesh Babu P, P. Ponmurugan, L. Senthamil, P. John Augustine, A. Govindarajan","doi":"10.1109/ICCMC53470.2022.9753843","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753843","url":null,"abstract":"In recent era, the supply chain management is becoming a complex valued network that offers a major competitive advantage over logistics and supply chain management. Despite its advantages, the complexity is becoming a challenge that should provide verification of sources, maintaining product visibility and monitoring while moving via supply chains. The adoption of Internet of Things (IoT) can support all these movements that tends to track and monitor the activities of the products moving in the chain network. Such optimization enables the operations to get optimized that includes manufacturing, warehousing and transportation. In addition, the transparency of the supply chains can be maintained via blockchain and when combined with IoT, it increases the effectiveness and efficacy of the supply chain","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"53 59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126192730","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 : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9754014
K. U. Kiran, D. Srikanth, P. Nair, S. Hasane Ahammad, K. Saikumar
In the present field of software applications, the prominently employed parameters for parameters control are the kinds of models such as cloud computing, machine learning, and big data analytics. So, in the current scenario, these are in high demand and are on-line with the trends for future decades as well. Nevertheless, as mentioned earlier, these models can access very low data and process speed. It is well known that the storage equipment’s for day-to-day monitoring serves at a higher cost and has hardware complexity, further leading towards rapid increment in dimensionality. Therefore, for the higher rate of dimensional data, the optimization approach of any variety would consume time to a greater extent. The concern issues are mostly related to the dimensionality with high data space instead of the low data space. A dimensional dropped approach is proposed in this paper in combinational with the Logistic regression (L.R.) version. The proposed technique is well known and applicable for the problems of clustering and dimension reduction. The size of the dimensional data to the LRML method has diminished, and the efficiency achieved at the rate of 95.5% and the reduction ratio is 34.89%.
{"title":"Dimensionality Reduction Procedure for Bigdata in Machine Learning Techniques","authors":"K. U. Kiran, D. Srikanth, P. Nair, S. Hasane Ahammad, K. Saikumar","doi":"10.1109/ICCMC53470.2022.9754014","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9754014","url":null,"abstract":"In the present field of software applications, the prominently employed parameters for parameters control are the kinds of models such as cloud computing, machine learning, and big data analytics. So, in the current scenario, these are in high demand and are on-line with the trends for future decades as well. Nevertheless, as mentioned earlier, these models can access very low data and process speed. It is well known that the storage equipment’s for day-to-day monitoring serves at a higher cost and has hardware complexity, further leading towards rapid increment in dimensionality. Therefore, for the higher rate of dimensional data, the optimization approach of any variety would consume time to a greater extent. The concern issues are mostly related to the dimensionality with high data space instead of the low data space. A dimensional dropped approach is proposed in this paper in combinational with the Logistic regression (L.R.) version. The proposed technique is well known and applicable for the problems of clustering and dimension reduction. The size of the dimensional data to the LRML method has diminished, and the efficiency achieved at the rate of 95.5% and the reduction ratio is 34.89%.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125297834","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 : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9754045
C. Subramanian, Nihar Ranjan Nayak, N. G N, D. K. Mohanty, S. Rout, S. K. Nandha Kumar
Nanotechnology is considered as a leading technology in controlling the agricultural process through monitoring with its miniature dimension. It therefore paves way for essential benefits on enhancing the quality and quantity of foods, reducing the input required for agricultural production, full utilization of soil nutrients, etc. The challenges in these models include availability of natural resources, sensing proper nutrients from the soil for crop-specific production, cultivation of crops. Hence, in this paper, various nano-sensors are utilized to increase the crop productivity by analyzing the nutrients present in the soil. The accuracy of acquisition and detection enables what type of crop can be used for cultivation or irrigation. The real-time nano sensors are deployed for absorbing the elements present in the soil that should suit the productivity of crop. The results of simulation using a deep learning detector based on the input from nano-sensors show an improved rate of productivity than state-of-art models.
{"title":"Use of Nanotechnology Sensors for Sustainable Agriculture","authors":"C. Subramanian, Nihar Ranjan Nayak, N. G N, D. K. Mohanty, S. Rout, S. K. Nandha Kumar","doi":"10.1109/ICCMC53470.2022.9754045","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9754045","url":null,"abstract":"Nanotechnology is considered as a leading technology in controlling the agricultural process through monitoring with its miniature dimension. It therefore paves way for essential benefits on enhancing the quality and quantity of foods, reducing the input required for agricultural production, full utilization of soil nutrients, etc. The challenges in these models include availability of natural resources, sensing proper nutrients from the soil for crop-specific production, cultivation of crops. Hence, in this paper, various nano-sensors are utilized to increase the crop productivity by analyzing the nutrients present in the soil. The accuracy of acquisition and detection enables what type of crop can be used for cultivation or irrigation. The real-time nano sensors are deployed for absorbing the elements present in the soil that should suit the productivity of crop. The results of simulation using a deep learning detector based on the input from nano-sensors show an improved rate of productivity than state-of-art models.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122858097","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 : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9754163
K. Nithya, S. Sathyapriya, M. Sulochana, S. Thaarini, C. R. Dhivyaa
Sentiment Analysis is the process of getting people’s ideas on what they think or feel about a particular issue or product or a person and classifying the information expressed about an issue in a positive, negative or a neutral manner. This extracted information can be found very much useful in determining popularity of a person or a product and they are very much useful in ecommerce in suggesting products to buy and in social media like YouTube in suggesting videos to view. Mostly people express their views and share their thoughts in their mother Tongue along with usage of mixed language words is common nowadays. Hence Sentiment analysis of codemixed language plays a major role. There is only little work available in Tamil mixed Sentiment analysis. In order to know the opinion of people who speak Tamil in an effective manner an effective algorithm is needed. Since there are many algorithms available in machine learning and deep learning, this work aims to find sentiment in code mixed words. Deep learning based Bi-LSTM model with ULMFiT Embedding gives more promising results for code-mixed language than other existing algorithms.
{"title":"Deep Learning based Analysis on Code-Mixed Tamil Text for Sentiment Classification with Pre-Trained ULMFiT","authors":"K. Nithya, S. Sathyapriya, M. Sulochana, S. Thaarini, C. R. Dhivyaa","doi":"10.1109/ICCMC53470.2022.9754163","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9754163","url":null,"abstract":"Sentiment Analysis is the process of getting people’s ideas on what they think or feel about a particular issue or product or a person and classifying the information expressed about an issue in a positive, negative or a neutral manner. This extracted information can be found very much useful in determining popularity of a person or a product and they are very much useful in ecommerce in suggesting products to buy and in social media like YouTube in suggesting videos to view. Mostly people express their views and share their thoughts in their mother Tongue along with usage of mixed language words is common nowadays. Hence Sentiment analysis of codemixed language plays a major role. There is only little work available in Tamil mixed Sentiment analysis. In order to know the opinion of people who speak Tamil in an effective manner an effective algorithm is needed. Since there are many algorithms available in machine learning and deep learning, this work aims to find sentiment in code mixed words. Deep learning based Bi-LSTM model with ULMFiT Embedding gives more promising results for code-mixed language than other existing algorithms.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"261 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122899894","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 : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9754051
Mohammad Sabih, D. Vishwakarma, Narendra Kumar
One of the most hotly debated aspects of human biometry is gait recognition. It entails understanding human propulsion without any physical touch, which makes it an effective biometric technique because it is difficult to mimic. However, images of persons captured are frequently discovered with a complex diversity of clothing and ambient statistics, resulting in a low identification rate in many occasions. The research presents a unique framework for learning the projections of two-dimensional optical flowfields. Rich optical streams are also collected, which are then adjusted using a moving average approach to keep the dispersed information over optical maps. Finally, a post-training Attention method is used to remedy the incorrect prediction, hence improving training ability. The suggested technique specifically handles self-occlusion scenarios in Gait recognition with a higher recognition rate and is evaluated on benchmark datasets, notably CASIA-B and OUM-VLP, outperforming many other existing state-of-the-art methods.
{"title":"Exploring Novel Optical Properties with Attention Mechanism for Gait Recognition","authors":"Mohammad Sabih, D. Vishwakarma, Narendra Kumar","doi":"10.1109/ICCMC53470.2022.9754051","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9754051","url":null,"abstract":"One of the most hotly debated aspects of human biometry is gait recognition. It entails understanding human propulsion without any physical touch, which makes it an effective biometric technique because it is difficult to mimic. However, images of persons captured are frequently discovered with a complex diversity of clothing and ambient statistics, resulting in a low identification rate in many occasions. The research presents a unique framework for learning the projections of two-dimensional optical flowfields. Rich optical streams are also collected, which are then adjusted using a moving average approach to keep the dispersed information over optical maps. Finally, a post-training Attention method is used to remedy the incorrect prediction, hence improving training ability. The suggested technique specifically handles self-occlusion scenarios in Gait recognition with a higher recognition rate and is evaluated on benchmark datasets, notably CASIA-B and OUM-VLP, outperforming many other existing state-of-the-art methods.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114407264","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 : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9753701
Ajan Ahmed, Mohammad Monirujjaman Khan
Based on the joint realization of financial technology and search algorithms, an online banking aggregation service was developed. A large database containing all data from participating financial institutions and precise search algorithms is the primary key behind the specific aggregation results. Users, regardless of occupation, position, or age, need to handle bank accounts, credit cards, and loans for different purposes. Using this algorithm, users can find the most suitable option for them.
{"title":"Development of a Web Based Online Financial Aggregator Service","authors":"Ajan Ahmed, Mohammad Monirujjaman Khan","doi":"10.1109/ICCMC53470.2022.9753701","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753701","url":null,"abstract":"Based on the joint realization of financial technology and search algorithms, an online banking aggregation service was developed. A large database containing all data from participating financial institutions and precise search algorithms is the primary key behind the specific aggregation results. Users, regardless of occupation, position, or age, need to handle bank accounts, credit cards, and loans for different purposes. Using this algorithm, users can find the most suitable option for them.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122054733","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 : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9753822
A. Veeramuthu, V. Kalist, A. A. Frank Joe, L. Megalan Leo, S. Yogalakshmi
Check-in data and photographs from journeys may be simply shared via social media. In light of the massive amount of social media data on user mobility, this work attempts to find travel experiences that might help plan a trip. When it comes to vacation planning, people always have a list of things they want to look for. As an alternative to limiting search options to places, activities, or time periods, arbitrary text descriptions are regarded as keywords that describe the individual demands of each user. It's also necessary to provide a wide variety of suggestions about how to go around. Previous research has focused on analyzing check-in data to identify and rank the most popular routes. According to us, additional POI characteristics should be retrieved in order to match the need for autonomous trip organizing. For the Keyword Representation Logic with Travel Route Suggestion Model (KRLTRSM) suggested in this research, knowledge extraction from users' historical mobility records as well as social interactions is used to give efficient keyword representation logic for search engines to employ (KRLTRSM). In order to effectively match query keywords with POI-related tags, we've created a KRLTRSM model explicitly. The method for reconstructing routes provided route candidates that matched the requirements specified. In order to provide acceptable query replies, representative Skyline concepts, or Skyline routes that best reflect the trade-offs between various POI qualities, are investigated. As shown by the experiment findings, these methodologies outperform existing state-of-the-art research based on extensive testing on real location-based social network datasets.
{"title":"Point of Interest Assisted Dynamic Travel Route Suggestion Model using Keyword Representation Logic","authors":"A. Veeramuthu, V. Kalist, A. A. Frank Joe, L. Megalan Leo, S. Yogalakshmi","doi":"10.1109/ICCMC53470.2022.9753822","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753822","url":null,"abstract":"Check-in data and photographs from journeys may be simply shared via social media. In light of the massive amount of social media data on user mobility, this work attempts to find travel experiences that might help plan a trip. When it comes to vacation planning, people always have a list of things they want to look for. As an alternative to limiting search options to places, activities, or time periods, arbitrary text descriptions are regarded as keywords that describe the individual demands of each user. It's also necessary to provide a wide variety of suggestions about how to go around. Previous research has focused on analyzing check-in data to identify and rank the most popular routes. According to us, additional POI characteristics should be retrieved in order to match the need for autonomous trip organizing. For the Keyword Representation Logic with Travel Route Suggestion Model (KRLTRSM) suggested in this research, knowledge extraction from users' historical mobility records as well as social interactions is used to give efficient keyword representation logic for search engines to employ (KRLTRSM). In order to effectively match query keywords with POI-related tags, we've created a KRLTRSM model explicitly. The method for reconstructing routes provided route candidates that matched the requirements specified. In order to provide acceptable query replies, representative Skyline concepts, or Skyline routes that best reflect the trade-offs between various POI qualities, are investigated. As shown by the experiment findings, these methodologies outperform existing state-of-the-art research based on extensive testing on real location-based social network datasets.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"33 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116594755","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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