Automatic web translators as part of a multilingual question-answering (QA) system: translation of questions
Metadata
Show full item recordMateria
Information retrieval Question-answering systems Machine translation Machine translation evaluation
Date
2010-01Referencia bibliográfica
García Santiago, L.; Olvera Lobo, M.D. Automatic web translators as part of a multilingual question-answering (QA) system: translation of questions. Translation Journal, 14(1): online(2010). [http://hdl.handle.net/10481/48373]
Abstract
The traditional model of information retrieval entails some implicit restrictions, including:
a) the assumption that users search for documents, not answers; and that the documents
per se will respond to and satisfy the query, and b) the assumption that the queries and
the document that will satisfy the particular informational need are written in the same
language. However, many times users will need specific data in response to the queries
put forth. Cross-language question-answering systems (QA) can be the solution, as they
pursue the search for a minimal fragment of text—not a complete document—that applies
to the query, regardless of the language in which the question is formulated or the
language in which the answer is found. Cross-language QA calls for some sort of
underlying translating process. At present there are many types of software for natural
language translation, several of them available online for free. In this paper we describe
the main features of the multilingual Question-Answering (QA) systems, and then analyze
the effectiveness of the translations obtained through three of the most popular online
translating tools (Google Translator, Promt and Worldlingo). The methodology used for
evaluation, on the basis of automatic and subjective measures, is specifically oriented
here to obtain a translation that will serve as input in a QA system. The results obtained
contribute to the realm of innovative search systems by enhancing our understanding of
online translators and their potential in the context of multilingual information retrieval.