Riadh Ben Messaoud, Omar Boussaid, Sabine Loudcher Rabaséda. Efficient multidimensional data representations based on multiple correspondence analysis. In Tina Eliassi-Rad, Lyle H. Ungar, Mark Craven, Dimitrios Gunopulos, editors, Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Philadelphia, PA, USA, August 20-23, 2006. pages 662-667, ACM, 2006. [doi]
@inproceedings{MessaoudBR06:1,
title = {Efficient multidimensional data representations based on multiple correspondence analysis},
author = {Riadh Ben Messaoud and Omar Boussaid and Sabine Loudcher Rabaséda},
year = {2006},
doi = {10.1145/1150402.1150484},
url = {http://doi.acm.org/10.1145/1150402.1150484},
tags = {rule-based, analysis, data-flow analysis},
researchr = {https://researchr.org/publication/MessaoudBR06%3A1},
cites = {0},
citedby = {0},
pages = {662-667},
booktitle = {Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Philadelphia, PA, USA, August 20-23, 2006},
editor = {Tina Eliassi-Rad and Lyle H. Ungar and Mark Craven and Dimitrios Gunopulos},
publisher = {ACM},
isbn = {1-59593-339-5},
}