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» Query Selectivity Estimation via Data Mining
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ICDE
2002
IEEE
146views Database» more  ICDE 2002»
15 years 10 months ago
Query Estimation by Adaptive Sampling
The ability to provide accurate and efficient result estimations of user queries is very important for the query optimizer in database systems. In this paper, we show that the tra...
Yi-Leh Wu, Divyakant Agrawal, Amr El Abbadi
AUSDM
2007
Springer
107views Data Mining» more  AUSDM 2007»
15 years 3 months ago
Preference Networks: Probabilistic Models for Recommendation Systems
Recommender systems are important to help users select relevant and personalised information over massive amounts of data available. We propose an unified framework called Prefer...
Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh
DIS
2004
Springer
15 years 2 months ago
Mining Noisy Data Streams via a Discriminative Model
The two main challenges typically associated with mining data streams are concept drift and data contamination. To address these challenges, we seek learning techniques and models ...
Fang Chu, Yizhou Wang, Carlo Zaniolo
75
Voted
DATAMINE
1999
80views more  DATAMINE 1999»
14 years 9 months ago
MSQL: A Query Language for Database Mining
The tremendous number of rules generated in the mining process makes it necessary for any good data mining system to provide for powerful query primitives to post-process the gener...
Tomasz Imielinski, Aashu Virmani
WWW
2011
ACM
14 years 4 months ago
Improving recommendation for long-tail queries via templates
The ability to aggregate huge volumes of queries over a large population of users allows search engines to build precise models for a variety of query-assistance features such as ...
Idan Szpektor, Aristides Gionis, Yoelle Maarek