An Adapted Lesk Algorithm for Word Sense Disambiguation Using WordNet

By Satanjeev Banerjee, Ted Pedersen. 2002

1,042 citations recorded by the source corpus.

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In Artificial Intelligence

Citations in the corpus

UNAL-NLP: Combining Soft Cardinality Features for Semantic Textual Similarity, Relatedness and Entailment (2014, methodology): “Next, the adapted Lesk algorithm (Banerjee and Pedersen, 2002) for word sense disambiguation was applied in the texts disambiguating one word at the time.”
Automatic Evaluation of Topic Coherence (2010, methodology): “Banerjee and Pedersen (2002) adapted this method to utilise WordNet sense glosses rather than dictionary definitions, and expand the dictionary definitions via ontological links, and it is this method we experiment with in this paper.”
A Survey of Text Similarity Approaches (2013, background): “Onge (hso) [33], Lesk (lesk) [34] and vector pairs (vector) [35].”
WordNet::Similarity - Measuring the Relatedness of Concepts (2004, methodology): “Our work with measures of semantic similarity and relatedness began while adapting the Lesk Algorithm for word sense disambiguation to WordNet (Banerjee and Pedersen, 2002).”
Free for All! Assessing User Data Exposure to Advertising Libraries on Android (2016, methodology): “Our prototype can be configured to use the following existing similarity metrics to disambiguate attribute matches: PATH [37]; LIN [30]; LCH [28]; LESK [6].”
Making Sense of Word Embeddings (2016, background): “Examples of such sys-tem include (Lesk, 1986; Banerjee and Pedersen, 2002; Pedersen et al., 2005; Moro et al., 2014) Unsupervised WSD approaches rely neither on hand-annotated sense-labeled corpora, nor on Figure 2: Visualization of the ego-network of “ta-ble” with furniture and data sense clusters.”
From Word to Sense Embeddings: A Survey on Vector Representations of Meaning (2018, neutral): “…Doherty, Evans, & Altendorf, 2016; Raganato, Delli Bovi, & Navigli, 2017b; Luo, Liu, Xia, Chang, & Sui, 2018) and knowledge-based (Lesk, 1986; Banerjee & Pedersen, 2002; Agirre, de Lacalle, & Soroa, 2014; Moro, Raganato, & Navigli, 2014; Tripodi & Pelillo, 2017; Chaplot & Salakhutdinov,…”
Using Measures of Semantic Relatedness for Word Sense Disambiguation (2003, methodology): “Banerjee and Pedersen suggest an adaptation based on the use of WordNet.”
Confidence Estimation for Machine Translation (2004, methodology): “The word-similarity function that was used here uses a dictionary-based approach developed by Banerjee & Pedersen [2].”
From distributional to semantic similarity (2004, methodology): “This work has been repeated using WORDNET glosses by Banerjee and Pederson (2002, 2003). Fox et al. (1988) extract a semantic network from two MRDs and Copestake (1990) extracts a taxonomy from the Longman’s Dictionary of Contemporary English.”
Name disambiguation in author citations using a K-way spectral clustering method (2005, methodology): “Existing word clustering methods we can apply include meth-ods based on the Word Net [7], distributional word clustering [6, 38, 14, 16], bipartite word clustering [53], committee-based word clustering [33], and other word similarity measures [46, 29] .”
Unsupervised Does Not Mean Uninterpretable: The Case for Word Sense Induction and Disambiguation (2017, neutral): “Classical examples of such approaches include (Banerjee and Pedersen, 2002; Pedersen et al., 2005; Miller et al., 2012).”
Measures of semantic similarity and relatedness in the biomedical domain (2007, methodology): “Additionally, these techniques have been shown to be useful for many Natural Language Processing tasks such as word sense disambiguation [10, 27 ], spelling correction [8] and information extraction [28].”
An Improved Model of Semantic Similarity Based on Lexical Co-Occurrence (2005, methodology): “The Adapted Lesk method (Banerjee & Pedersen, 2002) is a modified version of the Lesk algorithm (Lesk, 1986), for use with WordNet.”
Word sense disambiguation: a survey (2015, background): “In this approach [24, 25], First of all a short phrase (containing an ambiguous word) is selected from the sentence.”