Integrating Cyc and Wikipedia: Folksonomy meets rigorously defined common-sense

By Olena Medelyan, Catherine Legg. 2008

88 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Natural Language Processing

Citations in the corpus

Improving Question Answering with External Knowledge (2019, methodology): “A dictionary-based candidate generation approach (Medelyan and Legg, 2008) is adopted such that”
Unsupervised Entity Linking with Abstract Meaning Representation (2015, methodology): “We use commonness (Medelyan and Legg, 2008) as a measure of context independent salience for each mention m, to generate an initial ranked list of candidate entities E “ pe1, .”
An effective, low-cost measure of semantic relatedness obtained from Wikipedia links (2008, background): “This is the case for most applications in the literature, which deal primarily with topics: named entities (Bunescu and Pasca, 2006; Cucerzan, 2007); key phrases (Mihalcea and Csomai, 2007); categories (Gabrilovich and Markovitch, 2006); or entries in existing ontologies (Medelyan and Legg, 2008) an”
Learning multilingual named entity recognition from Wikipedia (2013, background): “Since Wikipedia does not have a direct source of entity types, there has been interest in mapping articles to existing ontologies such as WordNet [63,73,57] and Cyc [42], or classifying them into coarser schemes using heuristics [80,6,61] and semi-supervised [83,19,55] or fully supervised modelling ”
Mining Meaning from Wikipedia (2008, methodology): “Cyc to Wikipedia mappings 50,000 automatically created mappings from Cyc terms to Wikipedia articles (Medelyan and Legg, 2008) http://www.”
Commonsense Reasoning for Natural Language Understanding: A Survey of Benchmarks, Resources, and Approaches (2019, background): “More recently, there have been efforts to map Cyc to Wikipedia articles in an attempt to connect it to other resources such as DBpedia and Freebase (Medelyan & Legg, 2008; Pohl, 2012).”