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Markus Dickinson

dblp:70/5373 · DBLP profile ↗
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15ranked-venue papers
12as first author
0since 2021 · last 2013
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 15 · 12 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
3 papers
Information extraction and text analysis · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Natural language and speech › Information extraction and text analysis › data annotation › corpus annotation
syntactic annotation
0.122008
Ad Hoc Treebank Structures · ACL 2008
Detecting Errors in Discontinuous Structural Annotation · ACL 2005
Natural language and speech › Information extraction and text analysis
syntactic parsing
0.112010
Detecting Errors in Automatically-Parsed Dependency Relations · ACL 2010
Natural language and speech › Information extraction and text analysis › data annotation
annotation error detection
0.112005
Detecting Errors in Discontinuous Structural Annotation · ACL 2005
Natural language and speech › Information extraction and text analysis › data annotation
corpus annotation
0.112005
Detecting Errors in Discontinuous Structural Annotation · ACL 2005

Methods — techniques the papers use, named apart from their topics

variation n-gram error detection · 0.1
YearPublicationVenuePosition
2013 Detecting and Correcting Learner Korean Particle Omission Errors
Ross Israel, Markus Dickinson, Sun-Hee Lee
IJCNLP2
2012 Problems in Evaluating Grammatical Error Detection Systems
Martin Chodorow, Markus Dickinson, Ross Israel, Joel R. Tetreault
COLING2
2012 Annotating Errors in a Hungarian Learner Corpus
Markus Dickinson, Scott Ledbetter
LREC1
2012 Using semi-experts to derive judgments on word sense alignment: a pilot study
Soojeong Eom, Markus Dickinson, Graham Katz
LREC2
2010 Detecting Errors in Automatically-Parsed Dependency Relations
Markus Dickinson
ACL1
2010 Generating Learner-Like Morphological Errors in Russian
Markus Dickinson
COLING1
2010 Evaluating Distributional Properties of Tagsets
Markus Dickinson, Charles Jochim
LREC1
2009 Correcting Dependency Annotation Errors
Markus Dickinson
EACL1
2008 Ad Hoc Treebank Structures
Markus Dickinson
ACL1
2008 Representations for category disambiguation
Markus Dickinson
COLING1
2008 A Simple Method for Tagset Comparision
Markus Dickinson, Charles Jochim
LREC1
2008 Detecting Errors in Semantic Annotation
Markus Dickinson, Chong Min Lee
LREC1
2006 From Detecting Errors to Automatically Correcting Them
Markus Dickinson
EACL1
2005 Detecting Errors in Discontinuous Structural Annotation
abstract
Consistency of corpus annotation is an essential property for the many uses of annotated corpora in computational and theoretical linguistics. While some research addresses the detection of inconsistencies in positional annotation (e.g., part-of-speech) and continuous structural annotation (e.g., syntactic constituency), no approach has yet been developed for automatically detecting annotation errors in discontinuous structural annotation. This is significant since the annotation of potentially discontinuous stretches of material is increasingly relevant, from tree-banks for free-word order languages to semantic and discourse annotation.In this paper we discuss how the variation n-gram error detection approach (Dickinson and Meurers, 2003a) can be extended to discontinuous structural annotation. We exemplify the approach by showing how it successfully detects errors in the syntactic annotation of the German TIGER corpus (Brants et al., 2002).
Markus Dickinson, Detmar Meurers
ACL1
2003 Detecting Errors in Part-of-Speech Annotation
Markus Dickinson, Detmar Meurers
EACL1