Question-answering (QA) systems aim to provide answers for given questions. The can be extracted or generated from either unstructured structured text. Therefore, QA is considered an important field that used evaluate machine text understanding. Arabic a challenging language many reasons; although it spoken by more than 330 million native speakers, research on this limited. A few created are av...

Visual Question Answering (VQA) is an extremely stimulating and challenging research area where Computer Vision (CV) Natural Language Processig (NLP) have recently met. In image captioning video summarization, the semantic information completely contained in still images or dynamics, it has only to be mined expressed a human-consistent way. Differently from this, VQA same media must compared wi...

This paper reports on our progress towards building a Turkish Question Answering System to be used by distance education students of Anadolu University. We have converted 205 electronic books in PDF format to text, extracted metadata from these documents. Currently we provide search capabilities over these documents. Details on problems we faced, and solutions we came up with are provided. We a...

This paper describes the retrieval experiments for the main task and list task of the TREC-2002 question-answering track. The question answering system described automatically finds answers to questions in a large document collection. The system uses a two-stage retrieval approach to answer finding based on matching of named entities, linguistic patterns, keywords, and the use of a new inferenc...