@inproceedings{1cdb2395eece45cb84d81bd950ceeed9,
title = "Co-clustering for queries and corresponding advertisement",
abstract = "Both documents clustering and words clustering are well studied problems. Most existing algorithms cluster documents (advertisement) and words (query) separately but not simultaneously. In this paper we present a novel idea of analyzing both queries and advertisements which occur with queries at the same time. We present an innovative co-clustering algorithm that suggests queries by co-clustering advertisements and queries. We pose the co-clustering problem as an optimization problem in information theory - the optimal co-clustering maximizes the mutual information between the clustered random variables subject to constraints on the number of row and column clusters.",
keywords = "Co-clustering; online advertisement, Dbscan, K-mean clustering, Query, Singular value decomposition",
author = "Fan YANG and Bin AN and Xizhao WANG",
year = "2009",
doi = "10.1109/ICMLC.2009.5212131",
language = "English",
isbn = "9781424437023",
series = "International Conference on Machine Learning and Cybernetics (ICMLC)",
publisher = "IEEE",
pages = "2296--2299",
booktitle = "Proceedings of the 2009 International Conference on Machine Learning and Cybernetics",
note = "2009 International Conference on Machine Learning and Cybernetics ; Conference date: 12-07-2009 Through 15-07-2009",
}