A personalized privacy assistant app being developed can simplify the chore of setting permissions for smartphone apps. The privacy assistant can learn the user's preferences and quickly recommend the most appropriate settings, such as with which app to share the user's location, or contact list. The study has shown people's preferences can generally be organized in a small number of categories or "profiles" that differ based on people's willingness to grant different types of applications access to their information. The privacy assistant can determine to which of these categories a person belongs. Machine learning techniques enable the assistant to analyze a user's response to a small number of questions focusing on the particular apps they have on their phones. The privacy assistant recommended settings for the users, which they could accept or reject. But eventually the app may prove trustworthy enough to automatically make many of those decisions. Those using the privacy assistant adopted almost 80 percent of its privacy recommendations. Over the course of the study, participants changed only 5 percent of the settings that had originally been recommended to them by the personal privacy assistant. At the end of the study, these people indicated they were more comfortable with their privacy settings than users who did not have a privacy assistant. "Our findings suggest that the personal privacy assistant does a good job of properly profiling each user and that its recommendations based on those profiles were useful," Sadeh said. What can be inferred from this passage? A. Users have more control than before over their smart devices.B. The new findings are quite meaningful in computer science.C. The privacy assistant can accurately help set preferences.D. Users of the privacy assistant are supportive of the app.
A personalized privacy assistant app being developed can simplify the chore of setting permissions for smartphone apps. The privacy assistant can learn the user's preferences and quickly recommend the most appropriate settings, such as with which app to share the user's location, or contact list.
The study has shown people's preferences can generally be organized in a small number of categories or "profiles" that differ based on people's willingness to grant different types of applications access to their information. The privacy assistant can determine to which of these categories a person belongs. Machine learning techniques enable the assistant to analyze a user's response to a small number of questions focusing on the particular apps they have on their phones.
The privacy assistant recommended settings for the users, which they could accept or reject. But eventually the app may prove trustworthy enough to automatically make many of those decisions. Those using the privacy assistant adopted almost 80 percent of its privacy recommendations. Over the course of the study, participants changed only 5 percent of the settings that had originally been recommended to them by the personal privacy assistant. At the end of the study, these people indicated they were more comfortable with their privacy settings than users who did not have a privacy assistant.
"Our findings suggest that the personal privacy assistant does a good job of properly profiling each user and that its recommendations based on those profiles were useful," Sadeh said.
What can be inferred from this passage?
- A. Users have more control than before over their smart devices.
- B. The new findings are quite meaningful in computer science.
- C. The privacy assistant can accurately help set preferences.
- D. Users of the privacy assistant are supportive of the app.
题目解答
答案
解析
这段文字主要介绍了正在开发的一款个性化隐私助手应用程序，该程序可以简化为智能手机应用程序设置权限的繁琐任务。隐私助手可以通过学习用户的偏好，快速推荐最合适的设置，例如与哪些应用程序共享用户的位置或联系人列表。研究显示，人们的偏好可以大致归类为少数几个类别或“配置文件”，这些类别基于人们愿意授予不同类型应用程序访问其信息的意愿。隐私助手可以确定一个人属于这些类别中的哪一个。机器学习技术使助手能够分析用户对少数几个问题的回应，这些问题集中在他们手机上特定的应用程序上。隐私助手为用户推荐设置，用户可以选择接受或拒绝。但最终，该应用程序可能足够值得信赖，能够自动做出许多这些决定。使用隐私助手的用户采纳了其近80%的隐私推荐设置。在研究过程中，参与者只更改了最初由个人隐私助手推荐的5%的设置。研究结束时，这些用户表示他们对自己的隐私设置比没有使用隐私助手的用户更满意。“我们的研究结果表明，个人隐私助手在正确配置每个用户方面做得很好，基于这些配置文件的推荐设置非常有用，”Sadeh 说。
选项分析
A. Users have more control than before over their smart devices.
- 这个选项提到用户对智能设备的控制比以前更多。虽然隐私助手确实给了用户更多的控制权，但文章的重点是隐私助手如何简化设置权限的过程，而不是用户对设备的总体控制权。
B. The new findings are quite meaningful in computer science.
- 这个选项提到新发现对计算机科学很有意义。文章确实提到了机器学习技术的应用，但主要关注的是隐私助手的实际效果，而不是其在计算机科学领域的意义。
C. The privacy assistant can accurately help set preferences.
- 这个选项提到隐私助手可以准确地帮助设置偏好。文章中提到隐私助手通过学习用户的偏好来推荐设置，并且用户采纳了近80%的推荐设置，只更改了5%的设置，这表明隐私助手在帮助设置偏好方面是准确的。
D. Users of the privacy assistant are supportive of the app.
- 这个选项提到使用隐私助手的用户支持该应用程序。文章中提到用户采纳了近80%的推荐设置，并且在研究结束时表示他们对自己的隐私设置更满意，这表明用户对隐私助手的支持。
最佳答案
D. Users of the privacy assistant are supportive of the app.
详细解释
虽然选项 C 也符合文章的内容，但选项 D 更全面地反映了用户对隐私助手的态度。文章不仅提到用户采纳了大部分推荐设置，还提到用户在研究结束时表示对隐私设置更满意，这表明用户对隐私助手的支持和认可。因此，选项 D 是最合适的答案。
解析
本题考查对文章内容的推理和理解能力。解题思路是仔细分析文章中关于隐私助手的各项描述，然后逐一判断每个选项是否能从文章中合理推断出来。
- 选项A：文章重点在于隐私助手简化设置权限的过程，而非用户对智能设备的总体控制权，所以无法从文章中推断出用户对智能设备的控制比以前更多，该选项不符合文章内容。
- 选项B：文章主要关注隐私助手的实际效果，虽然提到了机器学习技术，但并没有强调其在计算机科学领域的意义，所以不能从文章中推断出新发现对计算机科学很有意义，该选项不符合文章内容。
- 选项C：文章提到隐私助手通过学习用户的偏好来推荐设置，并且用户采纳了近80%的推荐设置，只更改了5%的设置，这确实表明隐私助手在帮助设置偏好方面是准确的，但相比选项D，该选项不够全面地反映用户对隐私助手的态度。
- 选项D：文章中提到用户采纳了近80%的推荐设置，并且在研究结束时表示他们对自己的隐私设置更满意，这充分表明用户对隐私助手的支持和认可，所以可以从文章中推断出使用隐私助手的用户支持该应用程序，该选项符合文章内容。