Answer formulation for question-answering

被引：0

作者：

Kosseim, L

Plamondon, L

Guillemette, LJ

机构：

[1] Concordia Univ, Montreal, PQ H3G 1M8, Canada

[2] Univ Montreal, RALI, DIRO, Montreal, PQ H3C 3J7, Canada

来源：

ADVANCES IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS | 2003年 / 2671卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we describe our experimentations in evaluating 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 grammatical quality axe beneficial for both answer extraction and HCI.

引用

页码：24 / 34

页数：11

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