TY - JOUR
T1 - COPPER - Constraint optimized prefixspan for epidemiological research
AU - Guevara-Cogorno, Agustin
AU - Flamand, Claude
AU - Alatrista-Salas, Hugo
PY - 2015/1/1
Y1 - 2015/1/1
N2 - Sequential pattern mining, is a data mining technique used to study the temporal evolution of events describing a complex phenomenon. This technique has a limited application due to the high number of common sequences generated by dense datasets. To tackle this problem, we propose COP, an extension of the PrefixSpan algorithm oriented towards optimizing the relevance of the results obtained in the sequential patterns mining process. Indeed, we use multiple and simultaneous constraints that represent the expertise of researchers in a specific domain. Experiments conducted on datasets associated to dengue epidemic monitoring show an improve in result relevance from an expert's point of view, as well as, a considerable speed gains for mining dense datasets.
AB - Sequential pattern mining, is a data mining technique used to study the temporal evolution of events describing a complex phenomenon. This technique has a limited application due to the high number of common sequences generated by dense datasets. To tackle this problem, we propose COP, an extension of the PrefixSpan algorithm oriented towards optimizing the relevance of the results obtained in the sequential patterns mining process. Indeed, we use multiple and simultaneous constraints that represent the expertise of researchers in a specific domain. Experiments conducted on datasets associated to dengue epidemic monitoring show an improve in result relevance from an expert's point of view, as well as, a considerable speed gains for mining dense datasets.
KW - Constraints
KW - Epidemiological databases
KW - Healthcare risk management
KW - Sequential patterns mining
KW - Constraints
KW - Epidemiological databases
KW - Healthcare risk management
KW - Sequential patterns mining
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84954116180&origin=inward
UR - https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=84954116180&origin=inward
U2 - 10.1016/j.procs.2015.08.364
DO - 10.1016/j.procs.2015.08.364
M3 - Conference article
SN - 1877-0509
VL - 63
SP - 433
EP - 438
JO - Procedia Computer Science
JF - Procedia Computer Science
T2 - 5th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare, 2015
Y2 - 1 January 2015 through 1 January 2015
ER -