Question and answering service is one of the popular services in the World Wide Web. The main goal of these services is to finding the best answer for user's input question as quick as possible. In order to achieve this aim, most of these use new techniques foe question matching. . We have a lot of question and answering services in Persian web, so it seems that developing a question matching m...

This paper describes UAIC’s Question Answering for Machine Reading Evaluation systems participating in the QA4MRE 2011 evaluation task. The system is designed to extract knowledge from large volumes of text and to use this knowledge to answer questions in Romanian and English monolingual tasks. Our systems were built on the architecture of a Question Answering system, customized for this new ta...

In this paper, we present a new free resource for comparable Czech question answering evaluation. The Simple Question Answering Database, SQAD, contains 3301 questions and answers extracted and processed from the Czech Wikipedia. The SQAD database was prepared with the aim of a precision evaluation of automatic question answering systems. Such resource was currently not available for the Czech ...

Question-answering (QA) systems aim at providing either a small passage or just the answer to a question in natural language. We have developed several QA systems that work on both English and French. This way, we are able to provide answers to questions given in both languages by searching documents in both languages also. In this article, we present our French monolingual system FRASQUES whic...

In the QA and information retrieval domains progress has been assessed via evaluation campaigns(Clef, Ntcir, Equer, Trec).In these evaluations, the systems handle independent questions and should provide one answer to each question, extracted from textual data, for both open domain and restricted domain. Quæro is a program promoting research and industrial innovation on technologies for automat...

We study the problem of question topic classification using a very large real-world Community Question Answering (CQA) dataset from Yahoo! Answers. The dataset contains 3.9M questions and these questions are organized in more than one thousand categories in a hierarchy. To our best knowledge, this is the first systematic evaluation of the performance of different classification methods on quest...

This paper presents a multilayered Question Answering (QA) architecture suitable for enhancing current QA capabilities with the possibility of processing complex questions. That is, questions whose answer needs to be gathered from pieces of factual information that is scattered in different documents. Specifically, we have designed a specific layer oriented to process the different types of tem...

The paper briefly describes the First Shared Task Evaluation Challenge on Question Generation that took place in Spring 2010. The campaign included two tasks: Task A – Question Generation from Paragraphs and Task B – Question Generation from Sentences. An overview of each of the tasks is provided.

Existing studies of user acceptance factors try to provide answers to the questions of ‘why’, ‘what’, ‘who’, ‘when’ and ‘how’. In this paper, we propose to include the explicit question of ‘which’ into future evaluation studies. Two distinct approaches are discussed to address the question of ‘which’. The aim is not to show which is the best, but rather to demonstrate the potential of some alte...