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Ken Litkowski

dblp:148/4482 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2014
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 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
1 paper
Information extraction and text analysis · 62% Knowledge representation and reasoning · 38%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Natural language and speech › Information extraction and text analysis › lexical resources
lexical resource construction
0.212014
Pattern Dictionary of English Prepositions · ACL (1) 2014
Knowledge, reasoning and agents › Knowledge representation and reasoning
ontology
0.112014
Pattern Dictionary of English Prepositions · ACL (1) 2014
Knowledge, reasoning and agents › Knowledge representation and reasoning › ontology › lexical ontology
wordnet
0.112014
Pattern Dictionary of English Prepositions · ACL (1) 2014

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

dependency parsing · 0.2
YearPublicationVenuePosition
2014 Pattern Dictionary of English Prepositions
abstract
We present a new lexical resource for the study of preposition behavior, the Pattern Dictionary of English Prepositions (PDEP). This dictionary, which follows principles laid out in Hanks’ theory of norms and exploitations, is linked to 81,509 sentences for 304 prepositions, which have been made available under The Preposition Project (TPP). Notably, 47,285 sentences, initially untagged, provide a representative sample of preposition use, unlike the tagged sentences used in previous studies. Each sentence has been parsed with a dependency parser and our system has near-instantaneous access to features developed with this parser to explore and annotate properties of individual senses. The features make extensive use of WordNet. We have extended feature exploration to include lookup of FrameNet lexical units and VerbNet classes for use in characterizing preposition behavior. We have designed our system to allow public access to any of the data available in the system.
Ken Litkowski
ACL (1)1