Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
Ioannis Tsamardinos, Constantin F. Aliferis, Alexa...
Classification is an important data mining problem. Given a training database of records, each tagged with a class label, the goal of classification is to build a concise model ...
Johannes Gehrke, Venkatesh Ganti, Raghu Ramakrishn...
MapReduce is a popular framework for data-intensive distributed computing of batch jobs. To simplify fault tolerance, the output of each MapReduce task and job is materialized to ...
Tyson Condie, Neil Conway, Peter Alvaro, Joseph M....
The eXtensible Markup Language (XML) has become a ubiquitous data exchange and storage format. A variety of tools are available for incorporating XML-based data into applications....
Jules White, Boris Kolpackov, Balachandran Nataraj...
—The interference situation in the uplink of cellular networks, such as the 3GPP UTRAN Long Term Evolution (LTE), is usually highly volatile since from one transmission time inte...