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» Phenomenal Data Mining: From Data to Phenomena
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LREC
2010
203views Education» more  LREC 2010»
13 years 9 months ago
MPC: A Multi-Party Chat Corpus for Modeling Social Phenomena in Discourse
In this paper, we describe our experience with collecting and creating an annotated corpus of multi-party online conversations in a chat-room environment. This effort is part of a...
Samira Shaikh, Tomek Strzalkowski, Aaron Broadwell...
ICDM
2009
IEEE
134views Data Mining» more  ICDM 2009»
13 years 5 months ago
Efficient Discovery of Confounders in Large Data Sets
Given a large transaction database, association analysis is concerned with efficiently finding strongly related objects. Unlike traditional associate analysis, where relationships ...
Wenjun Zhou, Hui Xiong
PAKDD
2007
ACM
148views Data Mining» more  PAKDD 2007»
14 years 1 months ago
Mining Frequent Itemsets from Uncertain Data
Abstract. We study the problem of mining frequent itemsets from uncertain data under a probabilistic framework. We consider transactions whose items are associated with existential...
Chun Kit Chui, Ben Kao, Edward Hung
KDD
2010
ACM
247views Data Mining» more  KDD 2010»
13 years 9 months ago
Metric forensics: a multi-level approach for mining volatile graphs
Advances in data collection and storage capacity have made it increasingly possible to collect highly volatile graph data for analysis. Existing graph analysis techniques are not ...
Keith Henderson, Tina Eliassi-Rad, Christos Falout...
SSDBM
2005
IEEE
122views Database» more  SSDBM 2005»
14 years 1 months ago
Detection and Tracking of Discrete Phenomena in Sensor-Network Databases
This paper introduces a framework for Phenomena Detection and Tracking (PDT, for short) in sensor network databases. Examples of detectable phenomena include the propagation over ...
Mohamed H. Ali, Mohamed F. Mokbel, Walid G. Aref, ...