(Digital Academic
(Digital Academic
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发表时间：
2017
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通讯作者：
Inguna Skadin;Maria Eskevich;Lars Borin;Ilze Auzin;D. Broeder;Silvia Calamai;R. Gratta
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作者：
Inguna Skadin;Maria Eskevich;Lars Borin;Ilze Auzin;D. Broeder;Silvia Calamai;R. Gratta
我们如何更好地理解多回合信息寻求对话背后的机制？我们如何使用这些见解来设计一个对话系统，而不需要在回答问题时预先明确的查询公式？为了回答这些问题，我们收集了人类参与者执行类似任务的观察结果，以获得系统设计的灵感。然后，我们研究了在这些设置中发生的对话结构，并使用由此产生的见解来开发一个有根据的理论，设计和评估第一个系统原型。评估结果表明，该方法是有效的，可以补充基于查询的信息检索方法。我们通过分析和提供对一种信息寻求策略的自动化支持，为信息寻求行为提供了新的见解，这种策略在信息需求的清晰度和对集合内容的熟悉程度较低时是有效的。
How can we better understand the mechanisms behind multi-turn information seeking dialogues? How can we use these insights to design a dialogue system that does not require explicit query formulation upfront as in question answering? To answer these questions, we collected observations of human participants performing a similar task to obtain inspiration for the system design. Then, we studied the structure of conversations that occurred in these settings and used the resulting insights to develop a grounded theory, design and evaluate a first system prototype. Evaluation results show that our approach is effective and can complement query-based information retrieval approaches. We contribute new insights about information-seeking behavior by analyzing and providing automated support for a type of information-seeking strategy that is effective when the clarity of the information need and familiarity with the collection content are low.