Question Answering with Textual CBR

Knowledge Sources for Textual CBR Applications

Textual CBR applications address issues that have traditionally been dealt with in the Information Retrieval community, namely the handling of textual documents. As CBR is a knowledge-based technique, the question arises where items of knowledge may come from and how they might contribute to the implementation of a Textual CBR system. In this paper, we will show how various pieces of knowledge ...

A Case Based Reasoning Approach for Answer Reranking in Question Answering

In this document I present an approach to answer validation and reranking for question answering (QA) systems. A cased-based reasoning (CBR) system judges answer candidates for questions from annotated answer candidates for earlier questions. The promise of this approach is that user feedback will result in improved answers of the QA system, due to the growing case base. In the paper, I present...

On the Relationship of AURA Question-Answering and Textual Entailment

Advanced Community Question Answering Sites with Multimedia Answers

There are many question answer sites are available now a days. Community question answering sites are efficient when compare with the automate question answering sites. The drawback of available community question answering system is that it can only provide textual answer. In this paper, we propose a scheme that enriches the textual answer with multimedia data. Our scheme consists of four comp...

Experiments with Open-Domain Textual Question Answering

This paper describes the integration of several knowledge-based natural language processing techniques into a Question Answering system, capable of mining textual answers from large collections of texts. Surprizing quality is achieved when several lightweight knowledge-based NLP techniques comI)lement mostly shallow, surface-based approaclms.