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KDD
2004
ACM
624views Data Mining» more  KDD 2004»
15 years 5 months ago
Programming the K-means clustering algorithm in SQL
Using SQL has not been considered an efficient and feasible way to implement data mining algorithms. Although this is true for many data mining, machine learning and statistical a...
Carlos Ordonez
KDD
2004
ACM
209views Data Mining» more  KDD 2004»
16 years 12 days ago
Tracking dynamics of topic trends using a finite mixture model
In a wide range of business areas dealing with text data streams, including CRM, knowledge management, and Web monitoring services, it is an important issue to discover topic tren...
Satoshi Morinaga, Kenji Yamanishi
KDD
2004
ACM
106views Data Mining» more  KDD 2004»
16 years 12 days ago
Early detection of insider trading in option markets
"Inside information" comes in many forms: knowledge of a corporate takeover, a terrorist attack, unexpectedly poor earnings, the FDA's acceptance of a new drug, etc...
Steve Donoho
KDD
2004
ACM
136views Data Mining» more  KDD 2004»
16 years 12 days ago
A cross-collection mixture model for comparative text mining
In this paper, we define and study a novel text mining problem, which we refer to as Comparative Text Mining (CTM). Given a set of comparable text collections, the task of compara...
ChengXiang Zhai, Atulya Velivelli, Bei Yu
KDD
2004
ACM
144views Data Mining» more  KDD 2004»
16 years 12 days ago
IncSpan: incremental mining of sequential patterns in large database
Many real life sequence databases, such as customer shopping sequences, medical treatment sequences, etc., grow incrementally. It is undesirable to mine sequential patterns from s...
Hong Cheng, Xifeng Yan, Jiawei Han
Data Mining
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