Sentence similarity based on semantic nets and corpus statistics

By Yuhua Li, David McLean, Zuhair A. Bandar, J. O'Shea, Keeley A. Crockett. IEEE Transactions on Knowledge and Data Engineering, 2006

916 citations recorded by the source corpus.

Subfields: Artificial Intelligence

View Paper: https://www.semanticscholar.org/paper/58331d76610488c64ce104fbc361e30d8f0f8704

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In Artificial Intelligence

Citations in the corpus

Metrology for AI: From Benchmarks to Instruments (2019, methodology): “There are other similar datasets, such as (Rubenstein and Goodenough 1965) and (Li et al. 2006), as used by (Hassan and Mihalcea 2011).”
DLS@CU: Sentence Similarity from Word Alignment and Semantic Vector Composition (2015, background): “Early work on sentence similarity (Corley and Mihalcea, 2005; Mihalcea et al., 2006; Li et al., 2006; Islam and Inkpen, 2008) established the basic procedural framework under which most modern algorithms operate: computing sentence similarity as a mean of word similarities across the two input…”
Modeling Sentences in the Latent Space (2012, background): “STASIS (Li et al., 2006) 0.”
Evolution of Semantic Similarity—A Survey (2020, methodology): “• LiSent [50]: 65 sentence pairs were built using the dictionary definition of 65 word pairs used in R&G dataset.”
BIT at SemEval-2017 Task 1: Using Semantic Information Space to Evaluate Semantic Textual Similarity (2017, methodology): “For a long time, IC related methods were usually used as word similarity (Resnik, 1995; Jiang and Conrath, 1997; Lin, 1997) or word weight (Li et al., 2006; Han et al., 2013) rather than the core evaluation modules of sentence similarity methods (Wu and Huang, 2016).”
ECNU: One Stone Two Birds: Ensemble of Heterogenous Measures for Semantic Relatedness and Textual Entailment (2014, methodology): “, 2012; Malakasiotis and Androutsopoulos, 2007) which calculates similarities using surface strings at either character level or word level; (2) corpus-based method (Li et al., 2006) which measures word or sentence similarities using the information gained from large corpora, including Latent Semant”
SemEval-2012 Task 6: A Pilot on Semantic Textual Similarity (2012, methodology): “The first dataset includes 65 sentence pairs which correspond to the dictionary definitions for the 65 word pairs in Similarity(Rubenstein and Goodenough, 1965).”
Understanding Plagiarism Linguistic Patterns, Textual Features, and Detection Methods (2012, methodology): “On the other hand, SEM [14], [15] and FUZZY [16]–[19] methods incorporate different semantic features, thesaurus dictionaries , and lexical databases, such as WordNet.”