图 书 馆
优化的环境感知如何帮助解决网络上的信息过载问题How Optimized Environmental Sensing Helps Address Information Overload on the Web |
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| 课程网址: | http://videolectures.net/ijcai09_guestrin_iow/ |
| 主讲教师: | Tom Mitchell |
| 开课单位: | 卡内基梅隆大学 |
| 开课时间: | 2009-07-22 |
| 课程语种: | 英语 |
| 中文简介: |  在本次演讲中，我们解决了一个基本问题，该问题是使用传感器监控河流和湖泊的生态状况，将水带入我们的水龙头的管网或坐在椅子上的老年人的活动时出现的：我们应该将传感器放在哪里才能做出有效而可靠的预测？这样的感测问题通常是NP难的，并且在过去，经常使用没有理论上关于解决方案质量的保证的启发式方法。在本次演讲中，我们介绍了可以有效地找到针对大型复杂传感问题的最佳解决方案的算法。我们的算法基于以下重要洞察力：许多重要的传感问题均表现出亚模数，直观地降低了退货属性：添加传感器有助于减少迄今为止放置的传感器数量。除了确定放置传感器的最有用的位置之外，我们的算法还可以处理设置，传感器节点需要能够通过有损链路可靠地通信，使用移动机器人来收集数据或解决方案必须能够抵抗对手和传感器的情况失败。我们介绍了将我们的算法应用于几种现实世界中的传感任务的结果，包括使用机器人传感器进行环境监控，使用内置传感椅进行活动识别以及传感器放置竞赛。最后，我们得出了一个有趣的联系，该联系是用于水监控的传感器位置与应对网络上信息过载的挑战。作为这种连接的示例，我们解决了以下问题：选择要阅读的博客以了解网络上讨论的最大新闻，并个性化内容以减少博客界的喧嚣。 |
| 课程简介: | In this talk, we tackle a fundamental problem that arises when using sensors to monitor the ecological condition of rivers and lakes, the network of pipes that bring water to our taps, or the activities of an elderly individual when sitting on a chair: Where should we place the sensors in order to make effective and robust predictions? Such sensing problems are typically NP-hard, and in the past, heuristics without theoretical guarantees about the solution quality have often been used. In this talk, we present algorithms which efficiently find provably near-optimal solutions to large, complex sensing problems. Our algorithms are based on the key insight that many important sensing problems exhibit submodularity, an intuitive diminishing returns property: Adding a sensor helps more the fewer sensors we have placed so far. In addition to identifying most informative locations for placing sensors, our algorithms can handle settings, where sensor nodes need to be able to reliably communicate over lossy links, where mobile robots are used for collecting data or where solutions need to be robust against adversaries and sensor failures. We present results applying our algorithms to several real-world sensing tasks, including environmental monitoring using robotic sensors, activity recognition using a built sensing chair, and a sensor placement competition. We conclude with drawing an interesting connection between sensor placement for water monitoring and addressing the challenges of information overload on the web. As examples of this connection, we address the problem of selecting blogs to read in order to learn about the biggest stories discussed on the web, and personalizing content to turn down the noise in the blogosphere. |
| 关 键 词: | 传感器; 生态; 河流 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2021-02-16：nkq |
| 最后编审: | 2021-02-16：nkq |
| 阅读次数: | 3 |