Pub Date : 2022-06-06DOI: 10.20894/ijdmta.102.011.001.004
Shobha Rani B R
A resume is a record utilized by people to offer their historical past and ability sets. A record with a quick precis or listing approximately applicable training and experience. The resume or CV is normally the primary object that a capacity person encounters concerning the process seeker and is by and large used for screening applicants that are frequently observed via way of means of an interview, at the same time as in search of employment with inside the process seeks system and well-designed resume. The online job portal using Django will assist a person to construct his or her non-public commercial via the resume builder gadget to expand a resume with a process placement gadget. Many big employers use digital resume processing structures to deal with a big wide variety of resumes. Job portal commercials might also additionally direct candidates to email their resume to their business enterprise or go to their internet site and post a resume in digital format. Online jobs sought via famous websites are useful as they ve served for many years as a distinguished seek device for process seekers and employers alike. Despite their treasured application in linking employers with the capacity employees, the looking system and generation utilized by process-looking websites have now no longer saved tempo with the fast modifications in computing functionality and gadget intelligence. The Information and records retrieval strategies utilized by those websites mainly relies upon manually entered seek queries with a few superior similarity metrics for rating seek result.
{"title":"Online Resume Builder Using Django","authors":"Shobha Rani B R","doi":"10.20894/ijdmta.102.011.001.004","DOIUrl":"https://doi.org/10.20894/ijdmta.102.011.001.004","url":null,"abstract":"A resume is a record utilized by people to offer their historical past and ability sets. A record with a quick precis or listing approximately applicable training and experience. The resume or CV is normally the primary object that a capacity person encounters concerning the process seeker and is by and large used for screening applicants that are frequently observed via way of means of an interview, at the same time as in search of employment with inside the process seeks system and well-designed resume. The online job portal using Django will assist a person to construct his or her non-public commercial via the resume builder gadget to expand a resume with a process placement gadget. Many big employers use digital resume processing structures to deal with a big wide variety of resumes. Job portal commercials might also additionally direct candidates to email their resume to their business enterprise or go to their internet site and post a resume in digital format. Online jobs sought via famous websites are useful as they ve served for many years as a distinguished seek device for process seekers and employers alike. Despite their treasured application in linking employers with the capacity employees, the looking system and generation utilized by process-looking websites have now no longer saved tempo with the fast modifications in computing functionality and gadget intelligence. The Information and records retrieval strategies utilized by those websites mainly relies upon manually entered seek queries with a few superior similarity metrics for rating seek result.","PeriodicalId":414709,"journal":{"name":"International Journal of Data Mining Techniques and Applications","volume":"5 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125665791","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 : 2022-06-06DOI: 10.20894/ijdmta.102.011.001.001
Parashar B M, H. K.
In our nation, farming is the main support for economy. Indian families are depending on agriculture. The nation s GDP is basically concentrated on agriculture. It s far essential to improvize farming practices to fulfill the difficult necessi ties. The quick variations in crop charges are common place inside the market. These fluctuations in costs are specifically because of the previous methods. This results in varaiations in demand and additionally within the marketplace worth of a crop. As soon as the cost increases and farmers be afflicted by an investment deprivation after the worth reduces. It will lead the plants to become waste, turning into a drawback for purchasers. Farmers arenot aware about the call for inside the rising agricultural economy this is taking place. Farmers arenot any further seeking to utilize analytic to acquire data they want to realise workable insights and make clever choices. In other nations many of the farmers are start ing to move towards automatic cultivation. The choice tree set of rules are associated with the group of learning algorithms which might be supervised. Productiveness can be advanced by using expertise and forecasting growth expenses via machine learning. A logical crop rate predicting gadgets are able to provide cultivators possibilities which could advantage human beings in a bigger context.
{"title":"Crop Price Prediction Using Decision Tree","authors":"Parashar B M, H. K.","doi":"10.20894/ijdmta.102.011.001.001","DOIUrl":"https://doi.org/10.20894/ijdmta.102.011.001.001","url":null,"abstract":"In our nation, farming is the main support for economy. Indian families are depending on agriculture. The nation s GDP is basically concentrated on agriculture. It s far essential to improvize farming practices to fulfill the difficult necessi ties. The quick variations in crop charges are common place inside the market. These fluctuations in costs are specifically because of the previous methods. This results in varaiations in demand and additionally within the marketplace worth of a crop. As soon as the cost increases and farmers be afflicted by an investment deprivation after the worth reduces. It will lead the plants to become waste, turning into a drawback for purchasers. Farmers arenot aware about the call for inside the rising agricultural economy this is taking place. Farmers arenot any further seeking to utilize analytic to acquire data they want to realise workable insights and make clever choices. In other nations many of the farmers are start ing to move towards automatic cultivation. The choice tree set of rules are associated with the group of learning algorithms which might be supervised. Productiveness can be advanced by using expertise and forecasting growth expenses via machine learning. A logical crop rate predicting gadgets are able to provide cultivators possibilities which could advantage human beings in a bigger context.","PeriodicalId":414709,"journal":{"name":"International Journal of Data Mining Techniques and Applications","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114524401","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 : 2022-06-06DOI: 10.20894/ijdmta.102.011.001.002
AnaghaP Dixit
Augmented intelligence is revolutionizing the waybusinesses function on a day-to-day basis. ChatOps are one suchexample of how simple queries and activities, such as customerengagementorsalesoperations,can be handled without the involvement of a human. Chat Ops is the synthes is of client queries and an instantaneousinformationalexchangeinstrumentthatfacilitatesdevelopmentofsoftwareandoperationalmethodsinits transmission and execution. These are low-cost, computer-assistedprogramsthathelpincustomerserviceandanymodel of people management. ChatOps offer support at clients’convenience,irrespective of location hence an appeal to amultitude of people. Such a tool is reconstructing the way data isperceived,preventing it sover load and distilling information down to the most needed and practical elements. ChatOps inherentlymeans Conversational AI which uses NLP and other algorithmsthat compliment it and implements its functionalities. The bot istrained by having various intents as inputs, which provide the standard for the automated response. Alarge corpus of user input she lps the AI toget better at predictions and pattern matching. The more number of such inputs, the better trained machine model availabletouse.The intentslieonalargespectrum that could start off as simple chit chat to complicated instructions,while maintaininganinteractiveandcontinuousconversationflow.
{"title":"CONVERSATIONAL AI AND ARTIFICIAL NEURAL NETWORKS","authors":"AnaghaP Dixit","doi":"10.20894/ijdmta.102.011.001.002","DOIUrl":"https://doi.org/10.20894/ijdmta.102.011.001.002","url":null,"abstract":"Augmented intelligence is revolutionizing the waybusinesses function on a day-to-day basis. ChatOps are one suchexample of how simple queries and activities, such as customerengagementorsalesoperations,can be handled without the involvement of a human. Chat Ops is the synthes is of client queries and an instantaneousinformationalexchangeinstrumentthatfacilitatesdevelopmentofsoftwareandoperationalmethodsinits transmission and execution. These are low-cost, computer-assistedprogramsthathelpincustomerserviceandanymodel of people management. ChatOps offer support at clients’convenience,irrespective of location hence an appeal to amultitude of people. Such a tool is reconstructing the way data isperceived,preventing it sover load and distilling information down to the most needed and practical elements. ChatOps inherentlymeans Conversational AI which uses NLP and other algorithmsthat compliment it and implements its functionalities. The bot istrained by having various intents as inputs, which provide the standard for the automated response. Alarge corpus of user input she lps the AI toget better at predictions and pattern matching. The more number of such inputs, the better trained machine model availabletouse.The intentslieonalargespectrum that could start off as simple chit chat to complicated instructions,while maintaininganinteractiveandcontinuousconversationflow.","PeriodicalId":414709,"journal":{"name":"International Journal of Data Mining Techniques and Applications","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132755693","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 : 2022-06-06DOI: 10.20894/ijdmta.102.011.001.003
Anshuman Narayan, Abhishek Choudhary, Arnav Kumar
In this era of technology where everything is getting automated, we are still relying on the old method of using pen and registers for attendance. This project aims to automate the attendance process using biometrics. In this project, Face Recognition and fingerprint have been used to mark attendance of students. This is implemented using Arduino UNO and Raspberry pi as the controllers. A fingerprint sensor is connected with Arduino and camera module with Raspberry pi. First, finger is scanned and then face is recognised with with the help of database. Final attendance is accessed via the internet by the authorized personnel.
{"title":"Attendance management using face recognition and fingerprint","authors":"Anshuman Narayan, Abhishek Choudhary, Arnav Kumar","doi":"10.20894/ijdmta.102.011.001.003","DOIUrl":"https://doi.org/10.20894/ijdmta.102.011.001.003","url":null,"abstract":"In this era of technology where everything is getting automated, we are still relying on the old method of using pen and registers for attendance. This project aims to automate the attendance process using biometrics. In this project, Face Recognition and fingerprint have been used to mark attendance of students. This is implemented using Arduino UNO and Raspberry pi as the controllers. A fingerprint sensor is connected with Arduino and camera module with Raspberry pi. First, finger is scanned and then face is recognised with with the help of database. Final attendance is accessed via the internet by the authorized personnel.","PeriodicalId":414709,"journal":{"name":"International Journal of Data Mining Techniques and Applications","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126067285","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 : 2022-06-06DOI: 10.20894/ijdmta.102.011.001.006
Aishwarya Ms, Shobha Rani B R
Today, most large-scale conversational AI agents (e.g. Alexa, Siri, or Google Assistant) are built using manually annotated data to train the different components of the system. Typically, the accuracy of the ML models in these components are improved by manually transcribing and annotating data. As the scope of these systems increase to cover more scenarios and domains, manual annotation to improve the accuracy of these components becomes prohibitively costly and time- consuming. In this paper, a group of Amazon researchers propose a system that leverages user-system interaction feedback signals to automate learning without any manual annotation. Users here tend to modify a previous query in hopes of fixing an error in the previous turn to get the right results. These reformulations, which are often preceded by defective experiences caused by errors in ASR, NLU, ER or the application. In some cases, users may not properly formulate their requests (e.g. providing partial title of a song), but gleaning across a wider pool of users and sessions reveals the underlying recurrent patterns. The proposed self-learning system automatically detects the errors, generate reformulations and deploys fixes to the runtime system to correct different types of errors occurring in different components of the system. The results show that the approach is highly scalable, and able to learn reformulations that reduce Alexa-user errors by pooling anonymized data across millions of customers.
{"title":"Artificial Intelligence Driven Chatbot","authors":"Aishwarya Ms, Shobha Rani B R","doi":"10.20894/ijdmta.102.011.001.006","DOIUrl":"https://doi.org/10.20894/ijdmta.102.011.001.006","url":null,"abstract":"Today, most large-scale conversational AI agents (e.g. Alexa, Siri, or Google Assistant) are built using manually annotated data to train the different components of the system. Typically, the accuracy of the ML models in these components are improved by manually transcribing and annotating data. As the scope of these systems increase to cover more scenarios and domains, manual annotation to improve the accuracy of these components becomes prohibitively costly and time- consuming. In this paper, a group of Amazon researchers propose a system that leverages user-system interaction feedback signals to automate learning without any manual annotation. Users here tend to modify a previous query in hopes of fixing an error in the previous turn to get the right results. These reformulations, which are often preceded by defective experiences caused by errors in ASR, NLU, ER or the application. In some cases, users may not properly formulate their requests (e.g. providing partial title of a song), but gleaning across a wider pool of users and sessions reveals the underlying recurrent patterns. The proposed self-learning system automatically detects the errors, generate reformulations and deploys fixes to the runtime system to correct different types of errors occurring in different components of the system. The results show that the approach is highly scalable, and able to learn reformulations that reduce Alexa-user errors by pooling anonymized data across millions of customers.","PeriodicalId":414709,"journal":{"name":"International Journal of Data Mining Techniques and Applications","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115351042","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 : 2022-06-06DOI: 10.20894/ijdmta.102.011.001.005
Hemanth Kumar S K, Shobha Rani B R
The project aims to create a less time consuming and corrupt method of reporting traffic infractions. The idea also offers the ability to pay fines promptly and with mobile money. The project also modernises the way that the police record offences. At the moment, the traffic police manually record the specifics of an offence in a book. The tool will enable traffic cops to report an offence using their mobile devices, replacing the need for inefficient books. The projectalsoseekstofacilitatetheworkoflawenforcementbyenablingmembers of the public to report motorists who are behaving improperly on the road. The whole population has the ability to make messages public. Into day sone tierandtwo tiercities,trafficisamajorissue.Policeinvolvementintrafficmanagementincludescontrollingtraffic,enforcingtrafficlaws,andfiningdrivers who violate the law.
{"title":"Traffic offence Management System","authors":"Hemanth Kumar S K, Shobha Rani B R","doi":"10.20894/ijdmta.102.011.001.005","DOIUrl":"https://doi.org/10.20894/ijdmta.102.011.001.005","url":null,"abstract":"The project aims to create a less time consuming and corrupt method of reporting traffic infractions. The idea also offers the ability to pay fines promptly and with mobile money. The project also modernises the way that the police record offences. At the moment, the traffic police manually record the specifics of an offence in a book. The tool will enable traffic cops to report an offence using their mobile devices, replacing the need for inefficient books. The projectalsoseekstofacilitatetheworkoflawenforcementbyenablingmembers of the public to report motorists who are behaving improperly on the road. The whole population has the ability to make messages public. Into day sone tierandtwo tiercities,trafficisamajorissue.Policeinvolvementintrafficmanagementincludescontrollingtraffic,enforcingtrafficlaws,andfiningdrivers who violate the law.","PeriodicalId":414709,"journal":{"name":"International Journal of Data Mining Techniques and Applications","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116099219","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 : 2021-12-06DOI: 10.20894/ijdmta.102.010.002.002
M.Sivaneshwari Ms
The 21st century is all about advanced technology, offering state-of-the-art tools to help organizations optimize their productivity and achieve the business s bottom line. The same dogma applies to the education sector, with smart phones, cloud-based platforms, the internet of things (IoT), social networking sites, genetic research, supercomputers, student web portals. Educational institutions should use big data as a transformative tool for many aspects of education but crafting individual lessons and lesson plans are at the forefront. Big data visualization helps academic institutions to assess performance indicators in research and students progress along with offering an adaptive learning module the engine to work from. The education sector cannot streamline its operations without organizing the large volume of data collected every day. Educational institutions generate quintillion bytes of data every day. It is impossible to store, organize, analyze, and gain insights from complex data using conventional tools. So, this is where we need big data analytics tools and applications to accelerate data management processes. Advanced tools with intuitive user interfaces and dashboards allow streamlined collection, storage, retrieval, and analysis of students data. This work aims to use grading system with data analytics tools to identify students problems and gain insights to bring positivity to learning processes.
{"title":"Enhanced Grading system in Education using Statistical Data Analysis","authors":"M.Sivaneshwari Ms","doi":"10.20894/ijdmta.102.010.002.002","DOIUrl":"https://doi.org/10.20894/ijdmta.102.010.002.002","url":null,"abstract":"The 21st century is all about advanced technology, offering state-of-the-art tools to help organizations optimize their productivity and achieve the business s bottom line. The same dogma applies to the education sector, with smart phones, cloud-based platforms, the internet of things (IoT), social networking sites, genetic research, supercomputers, student web portals. Educational institutions should use big data as a transformative tool for many aspects of education but crafting individual lessons and lesson plans are at the forefront. Big data visualization helps academic institutions to assess performance indicators in research and students progress along with offering an adaptive learning module the engine to work from. The education sector cannot streamline its operations without organizing the large volume of data collected every day. Educational institutions generate quintillion bytes of data every day. It is impossible to store, organize, analyze, and gain insights from complex data using conventional tools. So, this is where we need big data analytics tools and applications to accelerate data management processes. Advanced tools with intuitive user interfaces and dashboards allow streamlined collection, storage, retrieval, and analysis of students data. This work aims to use grading system with data analytics tools to identify students problems and gain insights to bring positivity to learning processes.","PeriodicalId":414709,"journal":{"name":"International Journal of Data Mining Techniques and Applications","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115865113","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 : 2021-12-06DOI: 10.20894/ijdmta.102.010.002.003
Rossi Ms, Pledger Ms, Teixeira Ms
The education society was badly affected due to COVID 19 pandemic with educational organizations struggle to discover the solutions to open the door. Most of the educational Institutions plays a vital part for enriching the academic performance of students and refining the overall performance of education . In that situation online learning tools appeared as a biggest solution. Online learning provides many advantages for students those who want flexible while attending college. However pupils face more challenges in online classes and search for online learning solutions. This paper explore various issues met by students during online education. The purpose of this study was to examine the issues faced by college students as a result of online learning during COVID 19.
{"title":"A Survey on various issues met by College Students in Online Education during covid 19","authors":"Rossi Ms, Pledger Ms, Teixeira Ms","doi":"10.20894/ijdmta.102.010.002.003","DOIUrl":"https://doi.org/10.20894/ijdmta.102.010.002.003","url":null,"abstract":"The education society was badly affected due to COVID 19 pandemic with educational organizations struggle to discover the solutions to open the door. Most of the educational Institutions plays a vital part for enriching the academic performance of students and refining the overall performance of education . In that situation online learning tools appeared as a biggest solution. Online learning provides many advantages for students those who want flexible while attending college. However pupils face more challenges in online classes and search for online learning solutions. This paper explore various issues met by students during online education. The purpose of this study was to examine the issues faced by college students as a result of online learning during COVID 19.","PeriodicalId":414709,"journal":{"name":"International Journal of Data Mining Techniques and Applications","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125281856","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 : 2021-12-06DOI: 10.20894/ijdmta.102.010.002.004
Aparna Mr
Road accidental detection is one of the emerging issue in recent days, which has been focused by many researchers. Road accident is the major cause for unnatural death, and desirability, which is unpredictable. So, many existing works aimed to develop some prediction approaches for analyzing the real time dataset and predicting the accidental rate for future. But, it limits with the drawbacks like inefficient prediction, reduced accuracy, and increased time consumption. Thus, this paper aims to propose a new prediction model by implementing various data mining techniques. It includes the stages of preprocessing, clustering, and itemset mining. Initially, the dataset obtained from the UCI repository is preprocessed by eliminating the irrelevant attributes and filling the missing values. Then, the density based clustering technique is implemented to group the filtered data into a cluster. After that, the rules are formed based on the support and confidence values for predicting the future. Finally, the frequent items are mined by the use of Apriori algorithm. In experiments, the performance results of the proposed system is validated and evaluated by using various measures such as accuracy, precision, recall, and time consumption
{"title":"An Analysis of Road Accidental Data Using Clustering and Itemset Mining Algorithms","authors":"Aparna Mr","doi":"10.20894/ijdmta.102.010.002.004","DOIUrl":"https://doi.org/10.20894/ijdmta.102.010.002.004","url":null,"abstract":"Road accidental detection is one of the emerging issue in recent days, which has been focused by many researchers. Road accident is the major cause for unnatural death, and desirability, which is unpredictable. So, many existing works aimed to develop some prediction approaches for analyzing the real time dataset and predicting the accidental rate for future. But, it limits with the drawbacks like inefficient prediction, reduced accuracy, and increased time consumption. Thus, this paper aims to propose a new prediction model by implementing various data mining techniques. It includes the stages of preprocessing, clustering, and itemset mining. Initially, the dataset obtained from the UCI repository is preprocessed by eliminating the irrelevant attributes and filling the missing values. Then, the density based clustering technique is implemented to group the filtered data into a cluster. After that, the rules are formed based on the support and confidence values for predicting the future. Finally, the frequent items are mined by the use of Apriori algorithm. In experiments, the performance results of the proposed system is validated and evaluated by using various measures such as accuracy, precision, recall, and time consumption","PeriodicalId":414709,"journal":{"name":"International Journal of Data Mining Techniques and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116409129","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 : 2021-12-06DOI: 10.20894/ijdmta.102.010.002.001
Sangeetha.K Ms, Logeswari.P Ms, Rajeswari.S, Ms
The aim of this study is to merge the interval valued (int-valued) fuzzy graphs with fuzzy graphs of semi groups. We introduce the interval-valued fuzzy graph of semigroup (IVFGS) with some suitable examples and we study some of the properties of IVFGS and isomorphism of IVFGS
{"title":"INTERVAL–VALUED FUZZY GRAPH OF SEMI-GROUP","authors":"Sangeetha.K Ms, Logeswari.P Ms, Rajeswari.S, Ms","doi":"10.20894/ijdmta.102.010.002.001","DOIUrl":"https://doi.org/10.20894/ijdmta.102.010.002.001","url":null,"abstract":"The aim of this study is to merge the interval valued (int-valued) fuzzy graphs with fuzzy graphs of semi groups. We introduce the interval-valued fuzzy graph of semigroup (IVFGS) with some suitable examples and we study some of the properties of IVFGS and isomorphism of IVFGS","PeriodicalId":414709,"journal":{"name":"International Journal of Data Mining Techniques and Applications","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130402342","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：