Detecting Incorrect Numerical Data in DBpedia

Published on 2014-07-303479 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

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Presentation

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