Titlebook: Big Data Analytics; Proceedings of CSI 2 V. B. Aggarwal,Vasudha Bhatnagar,Durgesh Kumar Mis Conference proceedings 2018 Springer Nature Sin

果园

书目名称Big Data Analytics影响因子(影响力)




书目名称Big Data Analytics影响因子(影响力)学科排名




书目名称Big Data Analytics网络公开度




书目名称Big Data Analytics网络公开度学科排名




书目名称Big Data Analytics被引频次




书目名称Big Data Analytics被引频次学科排名




书目名称Big Data Analytics年度引用




书目名称Big Data Analytics年度引用学科排名




书目名称Big Data Analytics读者反馈




书目名称Big Data Analytics读者反馈学科排名

ILEUM

橡子

知识分子

A Framework for Ontology Learning from Taxonomic Data, very powerful tool for knowledge representation and literature also cites the conversion of taxonomies into ontologies. The automated ontology learning is developed to ward off the knowledge acquisition bottleneck; but thereof the limitation includes text understanding, knowledge extraction, struct

羞辱

Integrate

Hadoop: Solution to Unstructured Data Handling,as big data. 25% of the data that exist is in specified format, i.e., structured data and other 75% is in unspecified format. Unstructured data can be found anywhere. Generally, most of people and organizations pass out their lives working around unstructured data. In this paper, we have tried to wo

troponins

Task-Based Load Balancing Algorithm by Efficient Utilization of VMs in Cloud Computing,ng, it is trending Internet technology, which suffers from various issues and challenges. This research addresses load balancing as one of the major challenges in cloud computing. The paper proposes a dynamic load balancing algorithm for cloud computing environment and compares with the existing alg

镇压

A Load Balancing Algorithm Based on Processing Capacities of VMs in Cloud Computing,various types of services to the users in the form of hardware, software, application platforms. The cloud computing environment is elastic and heterogeneous in nature. Any number of users may join/leave the system at any point of time; it means the workload of the system increases/decreases randoml

朴素

angina-pectoris

Workload Prediction of E-business Websites on Cloud Using Different Methods of ANN,loads, data storage, service rate, processing time, etc. In this paper, author has tried to predict workload of e-business website on cloud-based environment. ANN-based approach is used by author to calculate number of cloud instances required to manage workload efficiently. Also different training