Demo Data from SIGIR 2026 / reviewers in the wild / expert
Ken Litkowski
dblp:148/4482
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Natural language and speech › Information extraction and text analysis › lexical resources
lexical resource construction |
0.2 | 1 | 2014 | Pattern Dictionary of English Prepositions · ACL (1) 2014 |
Knowledge, reasoning and agents › Knowledge representation and reasoning
ontology |
0.1 | 1 | 2014 | Pattern Dictionary of English Prepositions · ACL (1) 2014 |
Knowledge, reasoning and agents › Knowledge representation and reasoning › ontology › lexical ontology
wordnet |
0.1 | 1 | 2014 | Pattern Dictionary of English Prepositions · ACL (1) 2014 |
Methods — techniques the papers use, named apart from their topics
dependency parsing · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Pattern Dictionary of English PrepositionsabstractWe 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 |