AUTOWORDNET

The Automatic Generation of Lexical Databases Analogous to WordNet

Coordinatore	UNIVERSITE D'AIX MARSEILLE    more  Organization address address: Boulevard Charles Livon 58 city: Marseille postcode: 13284 contact info Titolo: Ms. Nome: Celine Cognome: Damon Email: send email Telefono: +33 4 91998595 Fax: +33 4 91998599
Nazionalità Coordinatore	France [FR]
Totale costo	258˙475 €
EC contributo	258˙475 €
Programma	FP7-PEOPLE Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
Code Call	FP7-PEOPLE-2010-IEF
Funding Scheme	MC-IEF
Anno di inizio	2012
Periodo (anno-mese-giorno)	2012-09-01   -   2014-08-31

 Partecipanti

#	participant	country	role	EC contrib. [€]
1	UNIVERSITE D'AIX MARSEILLE  Organization address address: Boulevard Charles Livon 58 city: Marseille postcode: 13284 contact info Titolo: Ms. Nome: Celine Cognome: Damon Email: send email Telefono: +33 4 91998595 Fax: +33 4 91998599	FR (Marseille)	coordinator	258˙475.00

Mappa

 Word cloud

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 Obiettivo del progetto (Objective)

'WordNet is a lexical database of English where words are grouped into sets of synonyms (synsets), each expressing a distinct concept. Synsets are interlinked by means of conceptual-semantic and lexical relations. WordNet has turned out to be an indispensable resource in the processing of natural language, and based on its model similar lexical databases were created for many other languages.

However, constructing such databases takes many years of work and is very costly. On the other hand, methods for the automatic identification of semantically related words based on large text corpora have reached a considerable degree of maturity, with the results coming close to native speakers’ performance. The proposed project aims at further refining and extending these approaches, thereby making it possible to fully automatically generate a resource similar to WordNet. The developed system will be largely language independent and is to be applied to four European languages, namely English, French, German, and Spanish. The resulting databases will be made freely available on the internet.

This is an outline of the proposed methodology: Starting from a part-of-speech tagged corpus, various methods for computing related words, such as syntax-based or utilizing latent semantic analysis, are applied and the results are systematically compared. The quality is evaluated by comparing the simulation results to a recently published data set comprising the 200,000 human similarity judgments from the Princeton Evocation project, rather than to the well established but inadequate 80 item TOEFL dataset. To identify synsets, an algorithm for unsupervised word sense induction is applied, and each word in the vocabulary is assigned to one or (if ambiguous) several of the synsets. Finally, to determine the relations between words (e.g. synonymy, hyponymy, holonymy, meronymy), an adapted version of Peter Turney’s approach for computing relational similarities is developed and applied.'