Answering Comparative Questions: Better than Ten-Blue-Links?
Matthias Schildw\"achter, Alexander Bondarenko, Julian Zenker,, Matthias Hagen, Chris Biemann, and Alexander Panchenko
TL;DR
This paper introduces CAM, an open-domain IR system that improves the accuracy and speed of answering comparative questions by argumentative comparison using data from the Common Crawl.
Contribution
CAM is a novel system that enhances comparative question answering by integrating argumentative comparison with large-scale web data.
Findings
15% more accurate answers with CAM
20% faster response times
Effective in open-domain comparative questions
Abstract
We present CAM (comparative argumentative machine), a novel open-domain IR system to argumentatively compare objects with respect to information extracted from the Common Crawl. In a user study, the participants obtained 15% more accurate answers using CAM compared to a "traditional" keyword-based search and were 20% faster in finding the answer to comparative questions.
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Taxonomy
TopicsTopic Modeling · Intelligent Tutoring Systems and Adaptive Learning · Speech and dialogue systems
MethodsClass-activation map