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Detecting Incorrect Numerical Data in DBpedia

Published on Jul 30, 20143472 Views

Heiko Paulheim

DBpedia is a central hub of Linked Open Data (LOD). Being based on crowd-sourced contents and heuristic extraction methods, it is not free of errors. In this paper, we study the application of unsuper

ESWC 2014 - Crete

Related categories

Big DataSemantic Web

Chapter list

Detecting Incorrect Numerical Data in DBpedia00:00
Motivation - 100:00
Motivation - 200:30
Motivation - 302:11
Idea03:50
Approach04:32
Median Absolute Deviation (MAD)04:58
Interquartile Range05:24
Kernel Density Estimation05:50
Approach - 106:18
Approach - 207:15
Evaluation08:03
Evaluation: Pre-study - 109:05
Evaluation: Pre-study - 209:30
Evaluation: Random sample - 110:11
Evaluation: Random sample - 211:05
Systematic Errors Found - 111:58
Systematic Errors Found - 213:08
Systematic Errors Found - 314:02
Limitations14:53
Beyond DBpedia15:43
Ongoing work16:41
Questions?18:39
Thank you!18:44