Accession Number ADA566568
Title Data Mining Meets HCI: Making Sense of Large Graphs.
Publication Date Jul 2012
Media Count 189p
Personal Author D. H. Chau
Abstract We have entered the age of big data. Massive datasets are now common in science, government and enterprises. Yet, making sense of these data remains a fundamental challenge. Where do we start our analysis. Where to go next. How to visualize our findings. We answers these questions by bridging Data Mining and Human-Computer Interaction (HCI) to create tools for making sense of graphs with billions of nodes and edges, focusing on (1) Attention Routing: we introduce this idea, based on anomaly detection, that automatically draws people's attention to interesting areas of the graph to start their analyses. We present three examples Polonium unearths malware from 37 billion machine- file relationships NetProbe fingers bad guys who commit auction fraud. (2) Mixed-Initiative Sensemaking: we present two examples that combine machine inference and visualization to help users locate next areas of interest: Apolo guides users to explore large graphs by learning from few examples of user interest; Graphite finds interesting subgraphs, based on only fuzzy descriptions drawn graphically. (3) Scaling Up: we show how to enable interactive analytics of large graphs by leveraging Hadoop, staging of operations, and approximate computation. This thesis contributes to data mining, HCI, and importantly their intersection, including: interactive systems and algorithms that scale theories that unify graph mining approaches; and paradigms that overcome fundamental challenges in visual analytics. Our work is making impact to academia and society: Polonium protects 120 million people worldwide from malware; NetProbe made headlines on CNN, WSJ and USA Today; Pegasus won an opensource software award; Apolo helps DARPA detect insider threats and prevent exfiltration. We hope our Big Data Mantra 'Machine for Attention Routing Human for Interaction' will inspire more innovations at the crossroad of data mining and HCI.
Keywords Data mining
Ebay auction fraud detection
Feldspar
Graph mining
Graphical models
Graphite
Hci(Human-computer interaction)
Information retrieval
Learning machines
Man computer interface
Polonium
Random walk
Symantec malware detection
Visualization


 
Source Agency Non Paid ADAS
NTIS Subject Category 62B - Computer Software
95D - Human Factors Engineering
Corporate Author Carnegie-Mellon Univ., Pittsburgh, PA. Machine Learning Dept.
Document Type Technical report
Title Note N/A
NTIS Issue Number 1307
Contract Number W911NF-09-2-0053

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