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Michael J. Pazzani
Michael J. Pazzani
Distinguished Principal Scientist
isi.edu의 이메일 확인됨 - 홈페이지
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On the optimality of the simple Bayesian classifier under zero-one loss
P Domingos, M Pazzani
Machine learning 29 (2-3), 103-130, 1997
47471997
Content-Based Recommendation Systems
MJ Pazzani
Springer Link, 2007
41612007
A framework for collaborative, content-based and demographic filtering
MJ Pazzani
Artificial intelligence review 13, 393-408, 1999
24981999
Dimensionality reduction for fast similarity search in large time series databases
E Keogh, K Chakrabarti, M Pazzani, S Mehrotra
Knowledge and information Systems 3, 263-286, 2001
22572001
Learning and revising user profiles: The identification of interesting web sites
M Pazzani, D Billsus
Machine learning 27, 313-331, 1997
20821997
Learning collaborative information filters.
D Billsus, MJ Pazzani
Icml 98, 46-54, 1998
19331998
An online algorithm for segmenting time series
E Keogh, S Chu, D Hart, M Pazzani
Proceedings 2001 IEEE international conference on data mining, 289-296, 2001
17242001
Locally adaptive dimensionality reduction for indexing large time series databases
E Keogh, K Chakrabarti, M Pazzani, S Mehrotra
Proceedings of the 2001 ACM SIGMOD international conference on Management of …, 2001
12612001
Syskill & Webert: Identifying interesting web sites
MJ Pazzani, J Muramatsu, D Billsus
AAAI/IAAI, Vol. 1, 54-61, 1996
12611996
Beyond independence: Conditions for the optimality of the simple bayesian classi er
P Domingos, M Pazzani
Proc. 13th Intl. Conf. Machine Learning, 105-112, 1996
12431996
Scaling up dynamic time warping for datamining applications
EJ Keogh, MJ Pazzani
Proceedings of the sixth ACM SIGKDD international conference on Knowledge …, 2000
11492000
Segmenting time series: A survey and novel approach
E Keogh, S Chu, D Hart, M Pazzani
Data mining in time series databases, 1-21, 2004
9622004
User modeling for adaptive news access
D Billsus, MJ Pazzani
User modeling and user-adapted interaction 10, 147-180, 2000
9432000
An enhanced representation of time series which allows fast and accurate classification, clustering and relevance feedback.
EJ Keogh, MJ Pazzani
Kdd 98, 239-243, 1998
8521998
A hybrid user model for news story classification
D Billsus, MJ Pazzani
UM99 User Modeling: Proceedings of the Seventh International Conference, 99-108, 1999
6921999
Machine learning for user modeling
GI Webb, MJ Pazzani, D Billsus
User modeling and user-adapted interaction 11, 19-29, 2001
6522001
Locally adaptive dimensionality reduction for indexing large time series databases
K Chakrabarti, E Keogh, S Mehrotra, M Pazzani
ACM Transactions on Database Systems (TODS) 27 (2), 188-228, 2002
5832002
Detecting group differences: Mining contrast sets
SD Bay, MJ Pazzani
Data mining and knowledge discovery 5, 213-246, 2001
5582001
Reducing misclassification costs
M Pazzani, C Merz, P Murphy, K Ali, T Hume, C Brunk
Machine Learning Proceedings 1994, 217-225, 1994
5421994
The utility of knowledge in inductive learning
M Pazzani, D Kibler
Machine learning 9, 57-94, 1992
5081992
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