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» A General Divide and Conquer Approach for Process Mining
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KDD
2007
ACM
182views Data Mining» more  KDD 2007»
15 years 11 months ago
Cleaning disguised missing data: a heuristic approach
In some applications such as filling in a customer information form on the web, some missing values may not be explicitly represented as such, but instead appear as potentially va...
Ming Hua, Jian Pei
KDD
2009
ACM
191views Data Mining» more  KDD 2009»
15 years 3 months ago
Improving data mining utility with projective sampling
Overall performance of the data mining process depends not just on the value of the induced knowledge but also on various costs of the process itself such as the cost of acquiring...
Mark Last
KDD
2009
ACM
239views Data Mining» more  KDD 2009»
15 years 11 months ago
Tell me something I don't know: randomization strategies for iterative data mining
There is a wide variety of data mining methods available, and it is generally useful in exploratory data analysis to use many different methods for the same dataset. This, however...
Heikki Mannila, Kai Puolamäki, Markus Ojala, ...
KDD
2004
ACM
207views Data Mining» more  KDD 2004»
15 years 11 months ago
Belief state approaches to signaling alarms in surveillance systems
Surveillance systems have long been used to monitor industrial processes and are becoming increasingly popular in public health and anti-terrorism applications. Most early detecti...
Kaustav Das, Andrew W. Moore, Jeff G. Schneider
CIKM
2003
Springer
15 years 4 months ago
Question answering from the web using knowledge annotation and knowledge mining techniques
We present a strategy for answering fact-based natural language questions that is guided by a characterization of realworld user queries. Our approach, implemented in a system cal...
Jimmy J. Lin, Boris Katz