Answer Category-Aware Answer Selection for Question Answering

Answer Formulation for Question-Answering

In this paper, we describe our experimentations in answer formulation for question-answering (QA) systems. In the context of QA, answer formulation can serve two purposes: improving answer extraction or improving human-computer interaction (HCI). Each purpose has different precision/recall requirements. We present our experiments for both purposes and argue that formulations of better linguisti...

Metadata-Aware Measures for Answer Summarization in Community Question Answering

This paper presents a framework for automatically processing information coming from community Question Answering (cQA) portals with the purpose of generating a trustful, complete, relevant and succinct summary in response to a question. We exploit the metadata intrinsically present in User Generated Content (UGC) to bias automatic multi-document summarization techniques toward high quality inf...

SVM Answer Selection for Open-Domain Question Answering

A Probabilistic Framework for Answer Selection in Question Answering

This paper describes a probabilistic answer selection framework for question answering. In contrast with previous work using individual resources such as ontologies and the Web to validate answer candidates, our work focuses on developing a unified framework that not only uses multiple resources for validating answer candidates, but also considers evidence of similarity among answer candidates ...

Answer Attenuation in Question Answering

Research in Question Answering (QA) has been dominated by the TREC methodology of black-box system evaluation. This makes it difficult to evaluate the effectiveness of individual components and requires human involvement. We have collected a set of answer locations within the AQUAINT corpus for a sample of TREC questions, in doing so we also analyse the ability of humans to retrieve answers. Ou...