In big data, the large number of missing values is a serious problem to compute the correct decision. This problem seriously affects the quality of information query, distorts data mining and analysis, and misleads the decisions. Therefore, in order…
In big data, the large number of missing values is a serious problem to compute the correct decision. This problem seriously affects the quality of information query, distorts data mining and analysis, and misleads the decisions. Therefore, in order…
In big data, the large number of missing values is a serious problem to compute the correct decision. This problem seriously affects the quality of information query, distorts data mining and analysis, and misleads the decisions. Therefore, in order…
Data has become necessary part of every individual, industry, economy, business function and organization. Miscellaneous industries, machines and institutions are expanding their analytical data at digital world at a very high rate. As this data set…
Big data analytics (BDA) applications are a new category of software applications that process large amounts of data using scalable parallel processing infrastructure to obtain hidden value. Hadoop is the most mature open-source big data analytics…
In big data, the large number of missing values is a serious problem to compute the correct decision. This problem seriously affects the quality of information query, distorts data mining and analysis, and misleads the decisions. Therefore, in order…
Data has become necessary part of every individual, industry, economy, business function and organization. Miscellaneous industries, machines and institutions are expanding their analytical data at digital world at a very high rate. As this data set…
In big data, the large number of missing values is a serious problem to compute the correct decision. This problem seriously affects the quality of information query, distorts data mining and analysis, and misleads the decisions. Therefore, in order…
MapReduce has become the standard model for supporting big data analytics. In particular, MapReduce job optimization has been widely considered to be crucial in the implementations of big data analytics. However, there is still a lack of guidelines…
Data has become necessary part of every individual, industry, economy, business function and organization. Miscellaneous industries, machines and institutions are expanding their analytical data at digital world at a very high rate. As this data set…
Video data has become the largest source of big data. Owing to video data's complexities, velocity, and volume, public security and other surveillance applications require efficient, intelligent runtime video processing. To address these challenges,…
Big data analytics (BDA) applications are software applications that process huge amounts of data using large-scale parallel processing infrastructure to obtain hidden value. Hadoop is the most mature open source BDA processing framework, which…
Nowadays, cloud computing plays an important role in the process of storing both structured and unstructured data. This contributed to a very large data growth on web servers, which has come to be called Big Data. Cloud computing technology is…
The Internet of Things (IoT) device is becoming universal domain and its success cannot be ignored, but its threats on IoT devices increases concurrently. The Cyber-attacks are becoming the component of IoT affecting user's life. The professionals…
Machine Learning (ML) is a powerful tool that can be used to make predictions on the future nature of data based on the past history. ML algorithms operate by building a model from input examples to make data-driven predictions or decisions for the…
Seismic inversion is an image formation process for the spatial structures and physical properties of underground rock strata according to the seismic data observed on the surface or in wells under the constraints of known geological laws and…
Currently, the exponential growth of biomedical data along with the complexities of managing high dimensionality, imbalanced distribution, sparse attributes instigates a difficult challenge of effectively applying functional networks as a new…