In TREC 2007, Language Computer Corporation explored how a new, semantically-rich framework for information retrieval could be used to boost the overall performance of the answer ...
Andrew Hickl, Kirk Roberts, Bryan Rink, Jeremy Ben...
In this paper, we describe ideas and related experiments of Tsinghua University IR group in TREC 2004 QA track. In this track, our system consists three components: Question analy...
Anticipating the availability of large questionanswer datasets, we propose a principled, datadriven Instance-Based approach to Question Answering. Most question answering systems ...
We regard answer extraction of Question Answering (QA) system as a classification problem, classifying answer candidate sentences into positive or negative. To confirm the feasibil...
This paper presents our bilingual question-answering system MUSCLEF. We underline the difficulties encountered when shifting from a mono to a cross-lingual system, then we focus o...
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: improvin...
This paper describes the architecture of a Bulgarian–Bulgarian question answering system — BulQA. The system relies on a partially parsed corpus for answer extraction. The que...
This paper describes a discussion-bot that provides answers to students’ discussion board questions in an unobtrusive and humanlike way. Using information retrieval and natural ...
Donghui Feng, Erin Shaw, Jihie Kim, Eduard H. Hovy