We propose a fast and accurate algorithm, VIF regression, for doing feature selection in
large regression problems. VIF regression is extremely fast; it uses a one-pass search over …

This paper presents BiPaR, a bilingual parallel novel-style machine reading comprehension
(MRC) dataset, developed to support multilingual and cross-lingual reading comprehension …

This article presents two probabilistic models for answering ranking in the multilingual
question-answering (QA) task, which finds exact answers to a natural language question …

JAVELIN I and II Systems at TREC 2005 Page 1 JAVELIN I and II Systems at TREC 2005 Eric
Nyberg, Robert Frederking, Teruko Mitamura, Matthew Bilotti, Kerry Hannan, Laurie …

In this paper, we describe the JAVELIN Cross Language Question Answering system, which
includes modules for question analysis, keyword translation, document retrieval, information …

Question Answering (QA) research has been conducted in many languages. Nearly all the
top performing systems use heavy methods that require sophisticated techniques, such as …

Given a user question, the goal of a Question Answering (QA) system is to retrieve answers
rather than full documents or even best-matching passages, as most Information Retrieval …

In this paper, we describe our adaptation of the JAVELIN system to Japanese question
answering for the NTCIR-6 QAC track. To establish a baseline Japaneseto-Japanese non …

In this paper, we propose a framework to answer questions of opinion type. The data source
is the web pages returned from the search engine. By using Bayes Classifier, the main texts …

Abstract Multilingual Question Answering systems are generally very complex, integrating
several submodules to achieve their result. Global metrics (such as average precision and …