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International Journal of Data Mining Techniques and Applications最新文献

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A Survey on the Analysis of Dissolved Oxygen Level in Water using Data Mining Techniques 利用数据挖掘技术分析水中溶解氧含量的研究进展
International Journal of Data Mining Techniques and Applications Pub Date : 2018-12-26 DOI: 10.20894/ijdmta.102.007.002.009
R. Arunkumar, T. Velmurugan
{"title":"A Survey on the Analysis of Dissolved Oxygen Level in Water using Data Mining Techniques","authors":"R. Arunkumar, T. Velmurugan","doi":"10.20894/ijdmta.102.007.002.009","DOIUrl":"https://doi.org/10.20894/ijdmta.102.007.002.009","url":null,"abstract":"Data Mining (DM) is a powerful and a new field having various techniques to analyses the recent real world problems. In DM, environmental mining is one of the essential and interesting research areas. DM enables to collect fundamental insights and knowledge from massive volume of environmental data. The water quality is determining the condition of water in the environment. It represents the concentration and state (dissolved or particulate) of some or all the organic and inorganic material present in the water, together with certain physical characteristics of the water. The Dissolved Oxygen (DO) is one of the important aspects of water quality. The DO is the quantity of gaseous oxygen (O2) incorporated into the water. The DO is essential for keeping the water organisms alive. The amount of DO level in the water can be detected by various methods. The data mining techniques are properly used to find DO Level in the different types of water. A number of DM methods used to analyze the DO level such as Multi-Layer Perceptron, Multivariate Linear Regression, Factor Analysis, and Feed Forward Neural Network. This survey work discusses about such type of methods, particularly used for the analysis of DO level elaborately. Finally, this research suggests the best DM method to find DO level in water by means of a comparative analysis.","PeriodicalId":414709,"journal":{"name":"International Journal of Data Mining Techniques and Applications","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126876767","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}
引用次数: 0
E-Agriculture A way to digitalization 电子农业——数字化之路
International Journal of Data Mining Techniques and Applications Pub Date : 2018-12-26 DOI: 10.20894/ijdmta.102.007.002.010
S. Anand, Sukita Shettigar, Suman S. Goudar, Aditi Ohol
{"title":"E-Agriculture A way to digitalization","authors":"S. Anand, Sukita Shettigar, Suman S. Goudar, Aditi Ohol","doi":"10.20894/ijdmta.102.007.002.010","DOIUrl":"https://doi.org/10.20894/ijdmta.102.007.002.010","url":null,"abstract":"Agricultural sector is the backbone of our country and it plays a vital role in the overall economic growth of our nation. India has about 59% of its total area for agricultural purpose. The contribution of agricultural sector to our GDP is about 17%. Advanced techniques or the betterment in the arena of agriculture will as certain to increase the competence of certain farming activities. In this paper we introduce a concept for smart farming which utilizes wireless sensor web technology with a web based application. This will play a crucial role in helping farmers. It will aim for the betterment in the facilities given to the farmers and by focussing on the measurement of production of the crops. With the help of data mining techniques and algorithms like K-nearest, decision tree we will gather each and every data related to the farming and it should be updated frequently so that farmers and the consumers will get the right knowledge of the respective crops and about the suitable equipments related to farming. Existing system are not so much efficient in displaying such data characteristics. Our main aim is to enhance the growth in the agriculture sector and make the existing system smarter so that the decision- maker can define the expansion of agriculture activities to empower the different forces in existing agriculture sector.","PeriodicalId":414709,"journal":{"name":"International Journal of Data Mining Techniques and Applications","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114600834","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}
引用次数: 0
Feature Based Underwater Fish Recognition Using SVM Classifier 基于SVM分类器的水下鱼类特征识别
International Journal of Data Mining Techniques and Applications Pub Date : 2018-06-14 DOI: 10.20894/ijdmta.102.007.001.011
Sunil Kumar, Umagowri Ms, Elangovan Mr
{"title":"Feature Based Underwater Fish Recognition Using SVM Classifier","authors":"Sunil Kumar, Umagowri Ms, Elangovan Mr","doi":"10.20894/ijdmta.102.007.001.011","DOIUrl":"https://doi.org/10.20894/ijdmta.102.007.001.011","url":null,"abstract":"An approach for underwater fish recognition based on wavelet transform is presented in this paper. This approach decomposes the input image into sub-bands by using the multi resolutional analysis known as Discrete Wavelet Transform (DWT). As each sub-band in the decomposed image contains useful information about the image, the mean values of every sub-band are assumed as features. This approach is tested on Underwater Photography - A Fish Database. The database contains 7953 pictures of 1458 different species. The database is considered for the classification based on Support Vector machine (SVM) classifier. The result shows that maximum recognition accuracy of 90.74% is achieved by the wavelet features.","PeriodicalId":414709,"journal":{"name":"International Journal of Data Mining Techniques and Applications","volume":"19 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113965279","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}
引用次数: 0
Hadoop and Hive Inspecting Maintenance of Mobile Application for Groceries Expenditure 杂货消费移动应用的Hadoop和Hive巡检维护
International Journal of Data Mining Techniques and Applications Pub Date : 2018-06-14 DOI: 10.20894/ijdmta.102.007.001.012
Rao Mr, Logeshwari Ms, Loganathan Mr
{"title":"Hadoop and Hive Inspecting Maintenance of Mobile Application for Groceries Expenditure","authors":"Rao Mr, Logeshwari Ms, Loganathan Mr","doi":"10.20894/ijdmta.102.007.001.012","DOIUrl":"https://doi.org/10.20894/ijdmta.102.007.001.012","url":null,"abstract":"Numerous movable applications on secure groceries expenditure and e-health have designed recently. Health aware clients respect such applications for secure groceries expenditure, particularly to avoid irritating groceries and added substances. However, there is the lack of a complete database including organized or unstructured information to help such applications. In the paper propose the Multiple Scoring Frameworks (MSF), a healthy groceries expenditure search service for movable applications using Hadoop and MapReduce (MR). The MSF works in a procedure behind a portable application to give a search service for data on groceries and groceries added substances. MSF works with similar logic from a web search engine (WSE) and it crawls over Web sources cataloguing important data for possible utilize in reacting to questions from movable applications. MSF outline and advancement are featured in the paper during its framework design, inquiry understanding, its utilization of the Hadoop/MapReduce infrastructure, and activity contents.","PeriodicalId":414709,"journal":{"name":"International Journal of Data Mining Techniques and Applications","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121654061","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}
引用次数: 0
A Clustering Based Collaborative and Pattern based Filtering approach for Big Data Application 大数据应用中一种基于聚类的协同与模式过滤方法
International Journal of Data Mining Techniques and Applications Pub Date : 2018-06-14 DOI: 10.20894/ijdmta.102.007.001.010
M. Masillamani, Chamberlain Mr, R.Rajesh Mr
{"title":"A Clustering Based Collaborative and Pattern based Filtering approach for Big Data Application","authors":"M. Masillamani, Chamberlain Mr, R.Rajesh Mr","doi":"10.20894/ijdmta.102.007.001.010","DOIUrl":"https://doi.org/10.20894/ijdmta.102.007.001.010","url":null,"abstract":"With web services developing and aggregating in application range, benefit revelation has turned into a hot issue for benefit organization and service management. Service clustering gives a promising approach to part the entire seeking space into little areas in order to limit the disclosure time successfully. In any case, semantic data is a basic component amid the entire arranging process. Current industrialized Web Service Portrayal Language (WSPL) does not contain enough data for benefit depiction. Thusly, a service clustering technique has been proposed, which upgrades unique WSPL report with semantic data by methods for Connected Open Information (COI). Examination based genuine service information has been performed, and correlation with comparable techniques has additionally been given to exhibit the adequacy of the strategy. It is demonstrated that using semantic data from COI improves the exactness of service grouping. Furthermore, it shapes a sound base for promote thorough preparing with semantic data.","PeriodicalId":414709,"journal":{"name":"International Journal of Data Mining Techniques and Applications","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134326195","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}
引用次数: 0
Branch Selection Recommendation for Higher Secondary Student using Data Mining Techniques 使用数据挖掘技术的高中生分支选择建议
International Journal of Data Mining Techniques and Applications Pub Date : 2018-03-15 DOI: 10.20894/ijdmta.102.007.001.014
P. Kuppan, S. Mohanambal, N. Suresh
{"title":"Branch Selection Recommendation for Higher Secondary Student using Data Mining Techniques","authors":"P. Kuppan, S. Mohanambal, N. Suresh","doi":"10.20894/ijdmta.102.007.001.014","DOIUrl":"https://doi.org/10.20894/ijdmta.102.007.001.014","url":null,"abstract":"","PeriodicalId":414709,"journal":{"name":"International Journal of Data Mining Techniques and Applications","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124834575","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}
引用次数: 0
Automated Detection of Diabetic Retinopathy using Medical Image Processing Techniques 利用医学图像处理技术自动检测糖尿病视网膜病变
International Journal of Data Mining Techniques and Applications Pub Date : 2018-03-15 DOI: 10.20894/IJDMTA.102.007.001.024
Tandon Ms, Aparna Mr
{"title":"Automated Detection of Diabetic Retinopathy using Medical Image Processing Techniques","authors":"Tandon Ms, Aparna Mr","doi":"10.20894/IJDMTA.102.007.001.024","DOIUrl":"https://doi.org/10.20894/IJDMTA.102.007.001.024","url":null,"abstract":"Glaucoma is an eye disease that can result in blindness if it is not detected and treated in proper time. Diabetic related eye diseases like Diabetic Retinopathy , Diabetic Maculopathy are major cause of blindness. Early detection of diabetic diseases plays an important role to prevent blindness. In last few years there are several researches done in medical image processing and detection from the fund us images such as Optic disk and the retinal vessels done in the automated detection of Diabetic retinopathy , Diabetic Maculopathy . This research paper represents the methods which are used in the automated detection of diabetic retinopathy. The recent methods used to detect the factors like hemorrhages and Micro Aneurysms are also discussed in this paper","PeriodicalId":414709,"journal":{"name":"International Journal of Data Mining Techniques and Applications","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126834209","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}
引用次数: 0
APRM to Isolate Behavior (Frequent or Infrequent) by using Cross-Organizational Process Mining APRM通过使用跨组织过程挖掘来隔离行为(频繁或不频繁)
International Journal of Data Mining Techniques and Applications Pub Date : 2018-03-15 DOI: 10.20894/IJDMTA.102.007.001.005
J. Pavithra, I. AnetteRegina
{"title":"APRM to Isolate Behavior (Frequent or Infrequent) by using Cross-Organizational Process Mining","authors":"J. Pavithra, I. AnetteRegina","doi":"10.20894/IJDMTA.102.007.001.005","DOIUrl":"https://doi.org/10.20894/IJDMTA.102.007.001.005","url":null,"abstract":"","PeriodicalId":414709,"journal":{"name":"International Journal of Data Mining Techniques and Applications","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129015597","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}
引用次数: 0
Text Mining Techniques in Data Mining – Review 数据挖掘中的文本挖掘技术综述
International Journal of Data Mining Techniques and Applications Pub Date : 2018-03-15 DOI: 10.20894/IJDMTA.102.007.001.029
C. Christys, S. Arivalagan
{"title":"Text Mining Techniques in Data Mining – Review","authors":"C. Christys, S. Arivalagan","doi":"10.20894/IJDMTA.102.007.001.029","DOIUrl":"https://doi.org/10.20894/IJDMTA.102.007.001.029","url":null,"abstract":"","PeriodicalId":414709,"journal":{"name":"International Journal of Data Mining Techniques and Applications","volume":"190 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123555912","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}
引用次数: 0
Design Space Investigation and Automatized Optimization Utilizing Data Mining and Machine Learning Strategies 利用数据挖掘和机器学习策略的设计空间调查和自动化优化
International Journal of Data Mining Techniques and Applications Pub Date : 2018-03-15 DOI: 10.20894/IJDMTA.102.007.001.001
M. Manju, Logeshwari, R. Loganathan
{"title":"Design Space Investigation and Automatized Optimization Utilizing Data Mining and Machine Learning Strategies","authors":"M. Manju, Logeshwari, R. Loganathan","doi":"10.20894/IJDMTA.102.007.001.001","DOIUrl":"https://doi.org/10.20894/IJDMTA.102.007.001.001","url":null,"abstract":"","PeriodicalId":414709,"journal":{"name":"International Journal of Data Mining Techniques and Applications","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128436013","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}
引用次数: 0
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