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WIREs Data Mining Knowl Discov
Impact Factor: 2.541
Wiley Interdisciplinary Reviews:
Data Mining and Knowledge Discovery
Volume 8 Issue 2 (March 2018)
Page 0 - 0

Overviews

A survey of incremental high‐utility itemset mining
Published Online: Jan 14 2018
DOI: 10.1002/widm.1242
Utility‐oriented pattern mining
Abstract Full article on Wiley Online Library:   HTML | PDF
A survey of evaluation methods for personal route and destination prediction from mobility traces
Published Online: Nov 17 2017
DOI: 10.1002/widm.1237
Predicting mobility patterns requires user‐specific accuracy measures that would take into account changing user behavior over time.
Abstract Full article on Wiley Online Library:   HTML | PDF

Advanced Reviews

Multilabel feature selection: A comprehensive review and guiding experiments
Published Online: Jan 05 2018
DOI: 10.1002/widm.1240
Graphical overview of the paper.
Abstract Full article on Wiley Online Library:   HTML | PDF
Evolutionary data mining and applications: A revision on the most cited papers from the last 10 years (2007–2017)
Published Online: Dec 20 2017
DOI: 10.1002/widm.1239
Evolutionary Data Mining.
Abstract Full article on Wiley Online Library:   HTML | PDF
Energy forecasting tools and services
Published Online: Dec 11 2017
DOI: 10.1002/widm.1235
Forecasts provide the only option for the correct planning and scheduling of the power grid. The ever increasing volume of forecasting tools and services makes it difficult to obtain even a general sense of what each tool or service offers. The present contribution provides an overview and categorization of several energy‐related forecasting tools and services.
Abstract Full article on Wiley Online Library:   HTML | PDF
Triangle counting in large networks: a review
Published Online: Oct 06 2017
DOI: 10.1002/widm.1226
Classification of triangle counting works.
Abstract Full article on Wiley Online Library:   HTML | PDF

Focus Article

Anomaly detection by robust statistics
Published Online: Nov 23 2017
DOI: 10.1002/widm.1236
Fitting a line to data with outliers: classical (red) and robust (blue).
Abstract Full article on Wiley Online Library:   HTML | PDF

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