印度海德拉巴CMR技术学院
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作者:Thota Siva Ratna Sai , Palvadi Srinivas Kumar
来源:[J].International Journal of Machine Learning and Networked Collaborative Engineering, 2018, Vol.01 (01), pp.09-16CMR
摘要:Expansive scale sensor structures are sent in various application ranges, and the information they gather are utilized as a bit of major specialist for fundamental foundations. Information are gushed from different sources through transitional dealing with focus focuses that tota...
作者:Simran Kaur , Rashmi Agarwal
来源:[J].International Journal of Machine Learning and Networked Collaborative Engineering, 2018, Vol.01 (01), pp.33-47CMR
摘要:The amount of unstructured text present in all electronic media is increasing periodically day after day. In order to extract relevant and succinct information, extraction algorithms are limited to entity relationships. This paper is compendium of different bootstrapping approach...
作者:Alberto Otero Marquez , Vicente García-Díaz
来源:[J].International Journal of Machine Learning and Networked Collaborative Engineering, 2018, Vol.01 (01), pp.17-22CMR
摘要:The Business Process Model and Notation (BPMN) is the standard used to represent in a graphical way business processes that take place in every kind of organization and business. This paper analyzes three suites, jBPM, Bonita and BPM.NET, which are used to model business processe...
作者:Vishal Dutt , Puja Sharma , Anshuman Kumar Gautam ...
来源:[J].International Journal of Machine Learning and Networked Collaborative Engineering, 2018, Vol.01 (01), pp.01-08CMR
摘要:In this paper we focused on the emerging trends and various approaches for carrying out analytics on clouds for Big Data application. It revolves around four important analytics and Big Data. We also discussed about the some of the real world challenges in this cloud and Big Data...
作者:Mihir Mohanty , Hemanta Kumar Palo
来源:[J].International Journal of Machine Learning and Networked Collaborative Engineering, 2017, Vol.01 (01), pp.01-08CMR
摘要:Advancement in the field of digital signal processing and modern machine learning (ML) approaches has witnessed substantial growth in biomedical engineering. The diagnostic power of these machines has grown manifolds mainly due to the exploration of effective and discriminate fea...

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