NERITS - A Machine Translation Mashup System Using Wikimeta and DBpedia

Autor:	Eric Wehrli, Luka Nerima, Kamel Nebhi
Rok vydání:	2013
Předmět:	Information retrieval Machine translation Exploit Mashup Computer science Linked data computer.software_genre Named Entity Recognition World Wide Web Comprehension Machine Translation Named-entity recognition ddc:410 Contextual information Web service computer Linked Open Data
Zdroj:	Advanced Information Systems Engineering ISBN: 9783642387081 ESWC (Satellite Events) The Semantic Web: ESWC 2013 Satellite Events pp. 312-318
DOI:	10.1007/978-3-642-41242-4_57
Popis:	Recently, Machine Translation (MT) has become a quite popular technology in everyday use through Web services such as Google Translate. Although the different MT approaches provide good results, none of them exploits contextual information like Named Entity (NE) to help user comprehension. In this paper, we present NERITS, a machine translation mashup system using semantic annotation from Wikimeta and Linked Open Data (LOD) provided by DBpedia. The goal of the application is to propose a cross-lingual translation by providing detailed information extracted from DBpedia about persons, locations and organizations in the mother tongue of the user. This helps at scaling the traditional multilingual task of machine translation to cross-lingual applications.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::668ee14b5ed885e00db4b6e0dc1581e1 https://doi.org/10.1007/978-3-642-41242-4_57 Zobrazit plný text záznamu