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» Data Mining: Machine Learning, Statistics, and Databases
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110
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KDD
2006
ACM
115views Data Mining» more  KDD 2006»
16 years 2 months ago
Aggregating time partitions
Partitions of sequential data exist either per se or as a result of sequence segmentation algorithms. It is often the case that the same timeline is partitioned in many different ...
Evimaria Terzi, Panayiotis Tsaparas, Taneli Mielik...
KDD
2004
ACM
170views Data Mining» more  KDD 2004»
16 years 2 months ago
Why collective inference improves relational classification
Procedures for collective inference make simultaneous statistical judgments about the same variables for a set of related data instances. For example, collective inference could b...
David Jensen, Jennifer Neville, Brian Gallagher
ICWSM
2009
14 years 11 months ago
Delta TFIDF: An Improved Feature Space for Sentiment Analysis
Mining opinions and sentiment from social networking sites is a popular application for social media systems. Common approaches use a machine learning system with a bag of words f...
Justin Martineau, Tim Finin
ADMA
2006
Springer
110views Data Mining» more  ADMA 2006»
15 years 5 months ago
Learning with Local Drift Detection
Abstract. Most of the work in Machine Learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
João Gama, Gladys Castillo
92
Voted
PKDD
2010
Springer
128views Data Mining» more  PKDD 2010»
15 years 3 days ago
Learning to Tag from Open Vocabulary Labels
Most approaches to classifying media content assume a fixed, closed vocabulary of labels. In contrast, we advocate machine learning approaches which take advantage of the millions...
Edith Law, Burr Settles, Tom M. Mitchell