Kaaviasudhan V S, Saran Nithish T S, K. S, N. Y. Devi
{"title":"A Study on Technology Causes a Gap Between Human Generation","authors":"Kaaviasudhan V S, Saran Nithish T S, K. S, N. Y. Devi","doi":"10.46610/jodmm.2022.v07i01.003","DOIUrl":null,"url":null,"abstract":"Technology creates the generation gap by how well older people can learn and use new technology. Each generation have different values and opinions. Due to innovation develop its leads to the generation gap. A difference in the attitude of people from different generations leads to lack of understanding. And also, generation gap is also referred to as difference in the point of view between young and old generations specially between parents and children.","PeriodicalId":43061,"journal":{"name":"International Journal of Data Mining Modelling and Management","volume":"222 1","pages":""},"PeriodicalIF":0.4000,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Data Mining Modelling and Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46610/jodmm.2022.v07i01.003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
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Abstract
Technology creates the generation gap by how well older people can learn and use new technology. Each generation have different values and opinions. Due to innovation develop its leads to the generation gap. A difference in the attitude of people from different generations leads to lack of understanding. And also, generation gap is also referred to as difference in the point of view between young and old generations specially between parents and children.
期刊介绍：
Facilitating transformation from data to information to knowledge is paramount for organisations. Companies are flooded with data and conflicting information, but with limited real usable knowledge. However, rarely should a process be looked at from limited angles or in parts. Isolated islands of data mining, modelling and management (DMMM) should be connected. IJDMMM highlightes integration of DMMM, statistics/machine learning/databases, each element of data chain management, types of information, algorithms in software; from data pre-processing to post-processing; between theory and applications. Topics covered include: -Artificial intelligence- Biomedical science- Business analytics/intelligence, process modelling- Computer science, database management systems- Data management, mining, modelling, warehousing- Engineering- Environmental science, environment (ecoinformatics)- Information systems/technology, telecommunications/networking- Management science, operations research, mathematics/statistics- Social sciences- Business/economics, (computational) finance- Healthcare, medicine, pharmaceuticals- (Computational) chemistry, biology (bioinformatics)- Sustainable mobility systems, intelligent transportation systems- National security
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