SciNet:一个通过关键字操作浏览科学文献的系统

D. Glowacka, Tuukka Ruotsalo, Ksenia Konyushkova, Kumaripaba Athukorala, Samuel Kaski, Giulio Jacucci
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引用次数: 3

摘要

探索性和已知条目搜索的技术倾向于只指向更具体的子主题或单个文档,而不允许对信息空间进行定向探索。我们介绍了SciNet,这是一个交互式信息检索系统,它结合了强化学习技术和新颖的用户界面设计,允许用户积极参与指导搜索。用户可以直接操纵文档特征(关键词)来表明他们的兴趣,强化学习通过允许系统在探索和利用之间进行权衡来对用户进行建模。这让用户有机会更有效地指导他们的搜索。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SciNet: a system for browsing scientific literature through keyword manipulation
Techniques for both exploratory and known item search tend to direct only to more specific subtopics or individual documents, as opposed to allowing directing the exploration of the information space. We present SciNet, an interactive information retrieval system that combines Reinforcement Learning techniques along with a novel user interface design to allow active engagement of users in directing the search. Users can directly manipulate document features (keywords) to indicate their interests and Reinforcement Learning is used to model the user by allowing the system to trade off between exploration and exploitation. This gives users the opportunity to more effectively direct their search.
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