Words worth attention: predicting words of the week on the Russian Wiktionary

Ustalov, Dmitry

DOI: https://doi.org/10.1007/978-3-319-11716-4_17
URL: https://www.researchgate.net/publication/265847308...
Additional URL: https://link.springer.com/chapter/10.1007/978-3-31...
Document Type: Conference or workshop publication
Year of publication: 2014
Book title: Knowledge Engineering and the Semantic Web : 5th International Conference, KESW 2014, Kazan, Russia, September 29–October 1, 2014. Proceedings
The title of a journal, publication series: Communications in Computer and Information Science
Volume: 468
Page range: 196-207
Conference title: Knowledge Engineering and the Semantic Web, KESW 2014
Location of the conference venue: Kazan, Russia
Date of the conference: September 29 - October 1, 2014
Publisher: Klinov, Pavel
Place of publication: Cham
Publishing house: Springer
ISBN: 978-3-319-11715-7 , 978-3-319-11716-4
ISSN: 1865-0929 , 1865-0937
Publication language: English
Institution: School of Business Informatics and Mathematics > Information Systems III: Enterprise Data Analysis (Ponzetto 2016-)
Subject: 004 Computer science, internet
Abstract: Such collaborative lexicography projects as Wiktionary are becoming strong competitors for traditional semantic resources just as Wikipedia has already become for expert-built knowledge bases. Keeping the data obtained from the general public crowd in good quality is a very challenging problem because of the fuzzy nature of the crowdsourcing phenomena. The presented study focuses on predicting the word of the week articles on the Russian Wiktionary by treating this problem as a binary classification task. The best proposed model is based on the Naïve Bayes classifier and has weighted average precision, recall, and F1-measure values of 87% by evaluating on the provided dataset.

Dieser Datensatz wurde nicht während einer Tätigkeit an der Universität Mannheim veröffentlicht, dies ist eine Externe Publikation.

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