The Quality of Lexical Semantic Resources: A Survey

With the increase of the lexical-semantic resources built over time, lexicon content quality has gained significant attention from Natural Language Processing experts such as lexicographers and linguists. Estimating lexicon quality components like synset lemmas, synset gloss, or synset relations are challenging research problems for Natural Language Processing. Several lexicon content quality approaches have been proposed over years in order to enhance the work of many applications such as machine translation, information retrieval, word sense disambiguation, data integration, and others. In this research, a survey for evaluation the quality of lexical semantic resources is presented.

[1]  Mustafa Jarrar,et al.  Position paper: towards the notion of gloss, and the adoption of linguistic resources in formal ontology engineering , 2006, WWW '06.

[2]  Fausto Giunchiglia,et al.  Regular Polysemy in WordNet and Pattern based Approach , 2013 .

[3]  Marek Maziarz,et al.  Expanding WordNet with Gloss and Polysemy Links for Evocation Strength Recognition , 2020, Cognitive Studies | Études cognitives.

[4]  Fausto Giunchiglia,et al.  Understanding and Exploiting Language Diversity , 2017, IJCAI.

[5]  Abed Alhakim Freihat An Organizational Approach to the Polysemy Problem in WordNet , 2014 .

[6]  Pushpak Bhattacharyya,et al.  Automatic Evaluation of Wordnet Synonyms and Hypernyms , 2008 .

[7]  Xiaojuan Ma Evocation: analyzing and propagating a semantic link based on free word association , 2013, Lang. Resour. Evaluation.

[8]  Yoshihiko Hayashi Predicting the Evocation Relation between Lexicalized Concepts , 2016, COLING.

[9]  Hugo Gonçalo Oliveira,et al.  Automatic Discovery of Fuzzy Synsets from Dictionary Definitions , 2011, IJCAI.

[10]  Rada Mihalcea,et al.  Building a Sense Tagged Corpus with Open Mind Word Expert , 2002, SENSEVAL.

[11]  Irene M. Cramer How Well Do Semantic Relatedness Measures Perform? A Meta-Study , 2008, STEP.

[12]  George A. Miller,et al.  Introduction to WordNet: An On-line Lexical Database , 1990 .

[13]  Fausto Giunchiglia,et al.  Compound Noun Polysemy and Sense Enumeration in WordNet , 2015 .

[14]  Jugal K. Kalita,et al.  Automatically constructing Wordnet Synsets , 2014, ACL.

[15]  Timothy Baldwin,et al.  Word sense and semantic relations in noun compounds , 2013, TSLP.

[16]  Laure Vieu,et al.  Towards semi-automatic methods for improving WordNet , 2011, IWCS.

[17]  Jeffrey Dean,et al.  Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.

[18]  P. Bhattacharyya,et al.  Towards Automatic Evaluation of Wordnet Synsets , 2007 .

[19]  Massimiliano Ciaramita,et al.  Supersense Tagging of Unknown Nouns in WordNet , 2003, EMNLP.

[20]  Fausto Giunchiglia,et al.  Solving specialization polysemy in WordNet , 2013 .

[21]  Vijay Mago,et al.  Evolution of Semantic Similarity—A Survey , 2020, ACM Comput. Surv..

[22]  Christiane Fellbaum,et al.  WordNet then and now , 2007, Lang. Resour. Evaluation.

[23]  Moch Arif Bijaksana,et al.  Building Synonym Set for Indonesian WordNet using Commutative Method and Hierarchical Clustering , 2020 .

[24]  Ziqi Zhang,et al.  Harnessing different knowledge sources to measure semantic relatedness under a uniform model , 2011, EMNLP.

[26]  Marti A. Hearst Automatic Acquisition of Hyponyms from Large Text Corpora , 1992, COLING.

[27]  On Hidden Semantic Relations between Nouns in WordNet , 2019, GWC.