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GCN : February 2013
30 GCN FEBRUARY 2013 • GCN.COM BIG DATA CASE STUDY DOCUMENTS AS MATH VECTORS Piranha essentially represents documents as mathematical vectors, which lets users of the software perform similarity comparisons, Po- tok explained. They can compare the two vectors and determine how closely they resemble each other. "What we are able to do in a highly parallel fashion is to create and compare these vectors, so in essence we are comparing every word in every document to every word in every other document," Potok said. From that point, researchers can say how similar the documents are. The Piranha clustering algorithm is similar to how animals are grouped in a genomic tree, Potok explained. "It kind of gives you a sense of how you look at similarities in documents, what things are similar or how things are dissimilar." Piranha's software agents work differently than more traditional software agents, Potok said. It is not a piece of software running around a network, but can be assigned to a specific computer or group of computers. For example, if an agency used the software with 10 computers, the software agents would move around the 10 computers to process information faster. A law enforcement officer might install Piranha on his computer, but not on any other. For an agency that has a huge volume of data, users might put Piranha on a cluster of computers, a very large cluster of computers or even on a supercomputer if they needed that level of computing power. ORNL's Computational Data Analytics Group is working to extend Piranha's capabilities. "We are looking to analyze a trillion docu- ments," Potok said, noting that the team is using the lab's supercom- puter to try to solve this task. But challenges still exist with how text analysis tools tag items, he said. An analyst might want to pull out and highlight a name in a doc- ument, for instance. But if he sees the name "Washington," he doesn't know if that refers to a person, city or street. ORNL's computational data analytics team is also focused on how to look at text information in a time view. For instance, with Twitter, people tweet things at certain times but also from certain locations. Law enforcement or intelligence analysts might already have certain information before an event occurs that could be significant, and af- ter the event wished that they had seen the information earlier. So the team is working on "how do you deal with time and location," Potok said. Finally, "perhaps one of the biggest challenges is: How do I deal with the volume of data and the ugliness of data?" Potok said. "You have all of these documents and raw information. Well, what is the value, what is useful and what is noise of no value at all?" • SPONSORED BY CDWG AND EMC BYOD TOPICS INCLUDE: BYOD PRESENTS BENEFITS, CHALLENGES FOR MOBILE STRATEGIES SECURITY, MANAGEMENT ISSUES THREATEN TO STALL BYOD IS BYOD REALLY THAT IMPORTANT TO MILLENNIALS? VIRTUALIZATION, ALREADY A MAJOR TREND, CAN HELP WITH BYOD IMPLEMENTING BYOD IS NOT EASY, BUT HERE ARE WAYS TO START Special Report TO LEARN MORE, VISIT: www.gcn.com/2013BYOD "This whole process now takes a matter of days instead of months." --- THOMAS POTOK, SENIOR SCIENTIST, COMPUTATIONAL DATA ANALYTICS GROUP AT OAK RIDGE