RAM^3S (Real-time Analysis of Massive MultiMedia Streams) is a framework that acts as a middleware software layer between multimedia stream analysis techniques and Big Data streaming platforms, so as to facilitate the implementation of the former on top of the latter. Indeed, the use of Big Data platforms can give way to the efficient management and analysis of large data amounts, but they require the user to concentrate on issues related to distributed computing since their services are often too raw. The use of RAM 3 S greatly simplifies deploying non-parallel techniques to platforms like Apache Storm or Apache Flink, a fact that is demonstrated by the four different use cases we describe here. We detail the lessons we learned from exploi...
The community of Big Data processing typically performs real-time computations on data streams with ...
Stream processing platforms allow applications to analyse incoming data continuously. Several use ca...
Content-based analysis tools not only have high complexity and costs, but they also neglect effectiv...
RAM^3S (Real-time Analysis of Massive MultiMedia Streams) is a framework that acts as a middleware s...
The real-time analysis of Big Data streams is a terrific resource for transforming data into value. ...
none2noThe real-time analysis of Big Data streams is a terrific resource for transforming data into v...
none2noFirst Online: 08 September 2017Big Data platforms provide opportunities for the management an...
Nowadays, Big Data platforms allow the analysis of massive data streams in an efficient way. However...
The avalanche of (both user- and device-generated) multimedia data published in online social networ...
Data processing frameworks based on cloud platforms are gaining significant attentionas solutions to...
Big-data is the expression used to describe large data sets, which are complex and require analysis ...
Next generation real-time applications demand big-data infrastructures to process huge and continuou...
© 2019 Association for Computing Machinery. All rights reserved. Processing high-volume, high-veloci...
The ever growing body of digital data is challenging conventional analytical techniques in machine l...
Summarization: The community of Big Data processing typically performs realtime computations on data...
The community of Big Data processing typically performs real-time computations on data streams with ...
Stream processing platforms allow applications to analyse incoming data continuously. Several use ca...
Content-based analysis tools not only have high complexity and costs, but they also neglect effectiv...
RAM^3S (Real-time Analysis of Massive MultiMedia Streams) is a framework that acts as a middleware s...
The real-time analysis of Big Data streams is a terrific resource for transforming data into value. ...
none2noThe real-time analysis of Big Data streams is a terrific resource for transforming data into v...
none2noFirst Online: 08 September 2017Big Data platforms provide opportunities for the management an...
Nowadays, Big Data platforms allow the analysis of massive data streams in an efficient way. However...
The avalanche of (both user- and device-generated) multimedia data published in online social networ...
Data processing frameworks based on cloud platforms are gaining significant attentionas solutions to...
Big-data is the expression used to describe large data sets, which are complex and require analysis ...
Next generation real-time applications demand big-data infrastructures to process huge and continuou...
© 2019 Association for Computing Machinery. All rights reserved. Processing high-volume, high-veloci...
The ever growing body of digital data is challenging conventional analytical techniques in machine l...
Summarization: The community of Big Data processing typically performs realtime computations on data...
The community of Big Data processing typically performs real-time computations on data streams with ...
Stream processing platforms allow applications to analyse incoming data continuously. Several use ca...
Content-based analysis tools not only have high complexity and costs, but they also neglect effectiv...