Predicting Heart Diseases from Large Scale IoT Data Using a Map-Reduce Paradigm

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Significant Big Data Interpretation using Map Reduce Paradigm

The development of ontologies involves continuous but relatively small modifications. Even after a number of changes, ontology and its previous versions usually share most of their axioms. For large and complex ontologies this may require a few minutes, or even a few hours. Cognitive on a Web scale becomes increasingly stimulating because of the large volume of data involved and the complexity ...

متن کامل

A Map-Reduce-enabled SOLAP cube for large-scale remotely sensed data aggregation

Spatial On-Line Analytical Processing (SOLAP) is a powerful decision support systems tool for exploring the multidimensional perspective of spatial data. In recent years, remotely sensed data have been integrated into SOLAP cubes, and this improvement has advantages in spatio-temporal analysis for environment monitoring. However, the performance of aggregations in SOLAP still faces a considerab...

متن کامل

Access control in ultra-large-scale systems using a data-centric middleware

  The primary characteristic of an Ultra-Large-Scale (ULS) system is ultra-large size on any related dimension. A ULS system is generally considered as a system-of-systems with heterogeneous nodes and autonomous domains. As the size of a system-of-systems grows, and interoperability demand between sub-systems is increased, achieving more scalable and dynamic access control system becomes an im...

متن کامل

Map-Reduce based Link Prediction for Large Scale Social Network

Link prediction is an important research direction in the field of Social Network Analysis. The significance of this research area is crucial especially in the fields of network evolution analysis and recommender system in online social networks as well as e-commerce sites. This paper aims at predicting the hidden links that are likely to occur in near future. The possibility of formation of li...

متن کامل

Mining Frequent Item Sets Using Map Reduce Paradigm

In Text categorization techniques like Text classification or clustering, finding frequent item sets is an acquainted method in the current research trends. Even though finding frequent item sets using Apriori algorithm is a widespread method, later DHP, partitioning, sampling, DIC, Eclat, FP-growth, H-mine algorithms were shown better performance than Apriori in standalone systems. In real sce...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Open Computer Science

سال: 2020

ISSN: 2299-1093

DOI: 10.1515/comp-2020-0204