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Axel Maroudas

dblp:67/3102 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2004
—ORCID · none

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

Artificial intelligence and machine learning · 1

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 · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Natural language and speech › Information extraction and text analysis › coreference resolution
bridging resolution		 0.012004
Learning to Resolve Bridging References · ACL 2004
Natural language and speech › Information extraction and text analysis
coreference resolution		 0.012004
Learning to Resolve Bridging References · ACL 2004

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

wordnet · 0.0machine learning · 0.0google · 0.0
YearPublicationVenuePosition
2004 Learning to Resolve Bridging References
abstract
We use machine learning techniques to find the best combination of local focus and lexical distance features for identifying the anchor of mereological bridging references.We find that using first mention, utterance distance, and lexical distance computed using either Google or WordNet results in an accuracy significantly higher than obtained in previous experiments.
Massimo Poesio, Rahul Mehta 0001, Axel Maroudas, Janet Hitzeman
 ACL3