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» Evaluating algorithms that learn from data streams
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KDD
2000
ACM
121views Data Mining» more  KDD 2000»
14 years 4 days ago
Mining high-speed data streams
Many organizations today have more than very large databases; they have databases that grow without limit at a rate of several million records per day. Mining these continuous dat...
Pedro Domingos, Geoff Hulten
ACL
2012
11 years 11 months ago
Named Entity Disambiguation in Streaming Data
The named entity disambiguation task is to resolve the many-to-many correspondence between ambiguous names and the unique realworld entity. This task can be modeled as a classifi...
Alexandre Davis, Adriano Veloso, Altigran Soares d...
ICDE
2008
IEEE
141views Database» more  ICDE 2008»
14 years 10 months ago
SPOT: A System for Detecting Projected Outliers From High-dimensional Data Streams
In this paper, we present a new technique, called Stream Projected Ouliter deTector (SPOT), to deal with outlier detection problem in high-dimensional data streams. SPOT is unique ...
Ji Zhang, Qigang Gao, Hai H. Wang
DIS
2010
Springer
13 years 7 months ago
Sentiment Knowledge Discovery in Twitter Streaming Data
Micro-blogs are a challenging new source of information for data mining techniques. Twitter is a micro-blogging service built to discover what is happening at any moment in time, a...
Albert Bifet, Eibe Frank
ICML
2005
IEEE
14 years 9 months ago
Learning predictive representations from a history
Predictive State Representations (PSRs) have shown a great deal of promise as an alternative to Markov models. However, learning a PSR from a single stream of data generated from ...
Eric Wiewiora