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KDD
2005
ACM
107views Data Mining» more  KDD 2005»
9 years 2 months ago
Cross-relational clustering with user's guidance
Clustering is an essential data mining task with numerous applications. However, data in most real-life applications are high-dimensional in nature, and the related information of...
Xiaoxin Yin, Jiawei Han, Philip S. Yu
KDD
2005
ACM
147views Data Mining» more  KDD 2005»
9 years 2 months ago
Combining proactive and reactive predictions for data streams
Mining data streams is important in both science and commerce. Two major challenges are (1) the data may grow without limit so that it is difficult to retain a long history; and (...
Ying Yang, Xindong Wu, Xingquan Zhu
KDD
2005
ACM
139views Data Mining» more  KDD 2005»
9 years 2 months ago
Learning to predict train wheel failures
This paper describes a successful but challenging application of data mining in the railway industry. The objective is to optimize maintenance and operation of trains through prog...
Chunsheng Yang, Sylvain Létourneau
KDD
2005
ACM
127views Data Mining» more  KDD 2005»
9 years 2 months ago
Mining closed relational graphs with connectivity constraints
Relational graphs are widely used in modeling large scale networks such as biological networks and social networks. In this kind of graph, connectivity becomes critical in identif...
Xifeng Yan, Xianghong Jasmine Zhou, Jiawei Han
KDD
2005
ACM
106views Data Mining» more  KDD 2005»
9 years 2 months ago
Enhancing the lift under budget constraints: an application in the mutual fund industry
A lift curve, with the true positive rate on the y-axis and the customer pull (or contact) rate on the x-axis, is often used to depict the model performance in many data mining ap...
Lian Yan, Michael Fassino, Patrick Baldasare
KDD
2005
ACM
222views Data Mining» more  KDD 2005»
9 years 2 months ago
Dynamic syslog mining for network failure monitoring
Kenji Yamanishi, Yuko Maruyama
KDD
2005
ACM
107views Data Mining» more  KDD 2005»
9 years 2 months ago
Predicting the product purchase patterns of corporate customers
This paper describes TIPPPS (Time Interleaved Product Purchase Prediction System), which analyses billing data of corporate customers in a large telecommunications company in orde...
Bhavani Raskutti, Alan Herschtal
KDD
2005
ACM
99views Data Mining» more  KDD 2005»
9 years 2 months ago
Disease progression modeling from historical clinical databases
This paper considers the problem of modeling disease progression from historical clinical databases, with the ultimate objective of stratifying patients into groups with clearly d...
Ronald K. Pearson, Robert J. Kingan, Alan Hochberg
KDD
2005
ACM
103views Data Mining» more  KDD 2005»
9 years 2 months ago
Key semantics extraction by dependency tree mining
We propose a new text mining system which extracts characteristic contents from given documents. We define Key semantics as characteristic sub-structures of syntactic dependencie...
Satoshi Morinaga, Hiroki Arimura, Takahiro Ikeda, ...
KDD
2005
ACM
149views Data Mining» more  KDD 2005»
9 years 2 months ago
A distributed learning framework for heterogeneous data sources
We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...
Srujana Merugu, Joydeep Ghosh
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