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ACQuA

Answering Comparative Questions with Arguments

In modern society, individuals are faced with choice problems on a daily basis. In the ACQuA project, we combine methods from natural language processing and information retrieval to design a new kind of argumentative machine for comparative question answering. Namely, the machine acts like a human expert in a respective field, taking a question as an input and suggesting the best object choice in the given context, supporting the answer with arguments. Similar to talking to human experts, interaction with the comparative argumentative machine is performed using natural language. To reach this goal, we propose a new approach involving several stages: (1) understanding comparative questions asked by users, (2) retrieving comparative argumentative structures relevant to a question from a web-scale text corpus, (3) gathering aspects of objects from a Wikipedia-based knowledge base enriched with aspects extracted from text, (4) comparison of objects on the basis of comparative argumentative structures and object aspects, (5) generation of arguments supporting the object choice, and (6) answer presentation. Prominent applications of the proposed comparative question answering approach are dialogue systems, decision support systems, and direct answers in web search engines.

[Demo   ]

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