CommunityCommands: command recommendations for software applications
CommunityCommands: command recommendations for software applications
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CommunityCommands：软件应用程序的命令建议
DOI：
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
G. Fitzmaurice
中科院分区：
文献类型：
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作者：
Justin Matejka;Wei Li;Tovi Grossman;G. Fitzmaurice
我们探讨使用现代推荐系统技术来解决学习软件应用的问题。在描述我们的新命令推荐系统之前，我们首先定义相关的设计考虑因素。然后，我们讨论了我们与专业用户进行的为期3个月的用户研究，以评估我们为每个用户生成定制推荐的算法。分析表明，我们的基于项目的协同过滤算法产生的2.1倍，许多好的建议，现有的技术。此外，我们提出了一个原型的用户界面，气氛目前的命令建议给用户，这已经收到了有前途的初步用户反馈。
We explore the use of modern recommender system technology to address the problem of learning software applications. Before describing our new command recommender system, we first define relevant design considerations. We then discuss a 3 month user study we conducted with professional users to evaluate our algorithms which generated customized recommendations for each user. Analysis shows that our item-based collaborative filtering algorithm generates 2.1 times as many good suggestions as existing techniques. In addition we present a prototype user interface to ambiently present command recommendations to users, which has received promising initial user feedback.