Using Wikipedia for Automatic Word Sense Disambiguation
By Rada Mihalcea. 2007
313 citations recorded by the source corpus.
Subfields: Information Retrieval & Search, Natural Language Processing
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Information Retrieval & Search
- Andras Csomai
- Armand Joulin
- Edouard Grave
- Piotr Bojanowski
- Tomas Mikolov
- Prakhar Gupta
- Chengfei Liu
- Shangfeng Hu
In Natural Language Processing
- Armand Joulin
- Edouard Grave
- Piotr Bojanowski
- Prakhar Gupta
- Douwe Kiela
- Hinrich Schütze
- Tomas Mikolov
- Graham Neubig
Citations in the corpus
- Learning Word Vectors for 157 Languages (2018, methodology): “English word vectors trained on a part of the Google News dataset (100B tokens) were published with word2vec (Mikolov et al., 2013b). Pennington et al. (2014) released GloVe models trained on Wikipedia, Gigaword and Common Crawl (840B tokens).”
- A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages (2020, neutral): “(Wu and Weld, 2010; Mihalcea, 2007; Al-Rfou et al., 2013; Bojanowski et al., 2017).”
- Incorporating Coreference Resolution into Word Sense Disambiguation (2011, background): “Many approaches [10, 11] are based on collocations [12].”
- Wikify!: linking documents to encyclopedic knowledge (2007, methodology): “The second approach is a data-driven method that integrates both local and topical features into a machine learning classifier [17].”