Sense inventory alignment using lexical substitutions and crowdsourcing

DOI:	https://doi.org/10.1109/FRUCT.2016.7584771
URL:	https://www.researchgate.net/publication/309150704...
Additional URL:	http://ieeexplore.ieee.org/document/7584771/
Document Type:	Conference or workshop publication
Year of publication:	2016
Book title:	Proceedings of the International FRUCT Conference on Intelligence, Social Media and Web (ISMW FRUCT 2016) : 28 August-4 September 2016, Saint-Petersburg, Russia
Page range:	56-61
Conference title:	2016 International FRUCT Conference on Intelligence, Social Media and Web (ISMW FRUCT)
Location of the conference venue:	Saint-Petersburg, Russia
Date of the conference:	August 28 - September 4, 2016
Publisher:	Balandin, Sergey
Place of publication:	Piscataway, NJ
Publishing house:	IEEE
ISBN:	978-1-5090-6187-7 , 978-952-68397-6-9 , 978-952-68397-7-6
Publication language:	English
Institution:	School of Business Informatics and Mathematics > Information Systems III: Enterprise Data Analysis (Ponzetto 2016-)
Subject:	004 Computer science, internet
Abstract:	Sense inventory induction is a topical problem of deriving a set of synsets representing concepts nsing various automatic or human-assisted methods. There might be, and actually are, mistakes in such synsets. Here we are focused on the problem of eliminating potentially duplicate synsets having exactly two words in common as the broader lntersectlon is known to be successfully addressed by beoristics. We exploit the pbenomena of lexical substitotions and microtaskbased crowdsourcing for aligning the synsets to the individual word senses. We also present an open source mobile application implementing oor approach. Our experiments on the Russian language show that the approach scales well aad dramatically reduces the number of duplicate synsets in the inventory.