Showing 1–12 of 74 results
A framework for processing large scale geospatial and remote sensing data in MapReduce environment Abstract?In recent years distributed data processing has reached many areas of computer science including geographic and remote sensing information systems. With the continuing increase of data, existing algorithms and data management need to be moved to new architecture, which may require…
A MapReduce-Based Nearest Neighbor Approach for Big-Data-Driven Traffic Flow Prediction Abstract? In big-data-driven traf c ow prediction systems, the robustness of prediction performance depends on accuracy and timeliness. This paper presents a new MapReduce-based nearest neighbor (NN) approach for traf c ow prediction using correlation analysis (TFPC) on a Hadoop platform. In particular, we develop a real-time…
A Security Model for Preserving the Privacy of Medical Big Data in a Healthcare Cloud Using a Fog Computing Facility with Pairing-Based Cryptography Abstract-Nowadays, telemedicine is an emerging healthcare service where the healthcare professionals can diagnose, evaluate,and treat a patient using telecommunication technology. To diagnose and evaluate a patient, the healthcare professionals need to access…
A survey of Big Data in social media using data mining techniques Abstract? World?s largest community Facebook?s ?Like? button pressed 2.7 billion times every day across the web revealing what people care about, such an impact of social media that internet user average almost spends 2.5 hours daily on liking, chatting, poking, tweeting on social…
Accelerating MapReduce on Commodity Clusters: An SSD-Empowered Approach Abstract? MapReduce, as a programming model and implementation for processing large data sets on clusters with hundreds or thousands of nodes, has gained wide adoption. In spite of the fact, we found that MapReduce on commodity clusters, which are usually equipped with limited memory and hard-disk drive…
Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore Abstract? We can use mobile phone call detail record (CDR) data, which contains millions of anonymous users, to extract individual mobility networks comparable to the activity-based approach. Such an approach is widely used in the transportation planning practice to develop urban…
An Efficient and Fine-grained Big Data Access Control Scheme with Privacy-preserving Policy Abstract? How to control the access of the huge amount of big data becomes a very challenging issue, especially when big data are stored in the cloud. Ciphertext-Policy Attribute-based Encryption (CP-ABE) is a promising encryption technique that enables end-users to encrypt their data…
An Efficient Privacy-Preserving Ranked Keyword Search Method Abstract?Cloud data owners prefer to outsource documents in an encrypted form for the purpose of privacy preserving. Therefore it is essential to develop efficient and reliable ciphertext search techniques. One challenge is that the relationship between documents will be normally concealed in the process of encryption, which will…
Analyzing Healthcare Big Data with Prediction for Future Health Condition Abstract– In healthcare management, a large volume of multi-structured patient data is generated from the clinical reports, doctor?s notes and wearable body sensors. The analysis of healthcare parameters and prediction of the subsequent future health conditions are still in informative stage. A cloud enabled big…
Apriori Versions Based on MapReduce for Mining Frequent Patterns on Big Data Abstract– Pattern mining is one of the most important tasks to extract meaningful and useful information from raw data. This task aims to extract item-sets that represent any type of homogeneity and regularity in data. Although many efficient algorithms have been developed in…
Automatic Brain Tumor Tissue Detection based on Hierarchical Centroid Shape Descriptor in T1-weighted MR images Abstract? The brain tumor tissue detection allows to localize a mass of abnormal cells in a slice of Magnetic Resonance (MR). The automatization of this process is useful for post processing of the extracted region of interest like the tumor…
BDCaM: Big Data for Context-aware Monitoring – A Personalized Knowledge Discovery Framework for Assisted Healthcare Abstract? BDCaM: Big Data for Context-aware Monitoring – A Personalized Knowledge Discovery Framework for Assisted Healthcare. Context-aware monitoring is an emerging technology that provides real-time personalised health-care services and a rich area of big data application. In this paper, we…
End of content
End of content
Don't have an account yet? Sign up
No items in your cart. Go on, fill it up with something you love!
Start Shopping Now
