?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=Data+Cube+Approximation+and+Mining+using+Probabilistic+Modeling&rft.creator=Goutte%2C+Cyril&rft.creator=Missaoui%2C+Rokia&rft.creator=Boujenoui%2C+Ameur&rft.subject=Machine+Learning&rft.subject=Artificial+Intelligence&rft.description=On-line+Analytical+Processing+(OLAP)+techniques+commonly+used+in+data+warehouses+allow+the+exploration+of+data+cubes+according+to+different+analysis+axes+(dimensions)+and+under+different+abstraction+levels+in+a+dimension+hierarchy.++However%2C+such+techniques+are+not+aimed+at+mining+multidimensional+data.%0A%0ASince+data+cubes+are+nothing+but+multi-way+tables%2C+we+propose+to+analyze+the+potential+of+two+probabilistic+modeling+techniques%2C+namely+non-negative+multi-way+array+factorization+and+log-linear+modeling%2C+with+the+ultimate+objective+of+compressing+and+mining+aggregate+and+multidimensional+values.+With+the+first+technique%2C+we+compute+the+set+of+components+that+best+fit+the+initial+data+set+and+whose+superposition+coincides+with+the+original+data%3B+with+the+second+technique+we+identify+a+parsimonious+model+(i.e.%2C+one+with+a+reduced+set+of+parameters)%2C+highlight+strong+associations+among+dimensions+and+discover+possible+outliers+in+data+cells.+A+real+life+example+will+be%0Aused+to+(i)+discuss+the+potential+benefits+of+the+modeling+output+on+cube+exploration+and+mining%2C+(ii)+show+how+OLAP+queries+can+be+answered+in+an+approximate+way%2C+and+(iii)+illustrate+the+strengths+and+limitations+of+these+modeling+approaches.%0A&rft.date=2007&rft.type=Departmental+Technical+Report&rft.type=NonPeerReviewed&rft.format=application%2Fpdf&rft.identifier=http%3A%2F%2Fcogprints.org%2F5622%2F1%2Fgoutte07datacube.pdf&rft.identifier=++Goutte%2C+Cyril+and+Missaoui%2C+Rokia+and+Boujenoui%2C+Ameur++(2007)+Data+Cube+Approximation+and+Mining+using+Probabilistic+Modeling.++%5BDepartmental+Technical+Report%5D+++++&rft.relation=http%3A%2F%2Fcogprints.org%2F5622%2F