组里同事Daan Odijk的文章 “Struggling and Success in Web Search”拿了CIKM 2015的 Best student paper。这个工作是他去年在MSR跟Ryen White和Susan Dumais 两个大牛合作的文章，具体工作的slides请看
摘要：
Web searchers sometimes struggle to find relevant information. Struggling leads to frustrating and dissatisfying search experiences, even if searchers ultimately meet their search objectives. Better understanding of search tasks where people struggle is important in improving search systems. We address this important issue using a mixed methods study using large-scale logs, crowd-sourced labeling, and predictive modeling. We analyze anonymized search logs from the Microsoft Bing Web search engine to characterize aspects of struggling searches and better explain the relationship between struggling and search success. To broaden our understanding of the struggling process beyond the behavioral signals in log data, we develop and utilize a crowd-sourced labeling methodology. We collect third-party judgments about why searchers appear to struggle and, if appropriate, where in the search task it became clear to the judges that searches would succeed (i.e., the pivotal query). We use our findings to propose ways in which systems can help searchers reduce struggling. Key components of such support are algorithms that accurately predict the nature of future actions and their anticipated impact on search outcomes. Our findings have implications for the design of search systems that help searchers struggle less and succeed more.
回复 ( 3 )
谢邀！
这个会议今天在墨尔本召开，持续一周！
会议来了很多学院派（清华大学、墨尔本大学、香港中文大学、阿姆斯特丹大学）、实战派（微软、谷歌、IBM、华为）、研究所等牛逼人物！
值得关注的亮点（如图）：
除了主题演讲，这些研讨会也很让人期待！
信息搜索、机器学习、数据分析等的分享都是值得关注的！
这是会议日程：
相比国内的会议，这个会议没有多少官方背景，基本上都是深处一线的研究者和实践者，会议开始也不是省长、书记、市长、某某副会长等的演讲，可以说肯定有很多干货，这从这些顶级分析嘉宾和赞助商就能够判断！
纯手打，有对大数据感兴趣的朋友欢迎加我们信微：idacker 里面有直达我个人号的方式。
谢邀，抱歉这么晚才来答，实在是因为。。。我看文章太慢。。。
题主问亮点。。。然而我能找到的亮点，起码是我能读懂的啊。。。于是。推荐一篇吧。
DeepCamera: A Unified Framework for Recognizing Places-of-Interest based on Deep ConvNets
好吧大概说一下这篇文章。其实做了个很简单的东西，你出去旅游，诶呀妈呀看到一建筑贼气派，拿出相机狂赤狂赤一顿照，还发朋友圈各种炫耀“身在异乡，只有这雄伟的古迹能让我暂时忘却心中淡淡的乡愁。”感觉一下高了好几个逼格。谁知道有个朋友秒回，“哥们儿，这是公厕”。。。
好吧，段子写完了，其实文章就是做了个根据图片识别建筑或者是地点的东西。这么一说感觉很简单，不过他是用CNN做的，而且移植到了智能机上，好吧，其实内核还是很简单。但是有卖点啊！DeepCamera！多酷炫
值得一提的是，这里的CNN加入了一个空间层，其实就是构建了一个基于fov的POI的概率分布空间。好吧，这个有点意思。。。
组里同事Daan Odijk的文章 “Struggling and Success in Web Search”拿了CIKM 2015的 Best student paper。这个工作是他去年在MSR跟Ryen White和Susan Dumais 两个大牛合作的文章，具体工作的slides请看
摘要：
Web searchers sometimes struggle to find relevant information. Struggling leads to frustrating and dissatisfying search experiences, even if searchers ultimately meet their search objectives. Better understanding of search tasks where people struggle is important in improving search systems. We address this important issue using a mixed methods study using large-scale logs, crowd-sourced labeling, and predictive modeling. We analyze anonymized search logs from the Microsoft Bing Web search engine to characterize aspects of struggling searches and better explain the relationship between struggling and search success. To broaden our understanding of the struggling process beyond the behavioral signals in log data, we develop and utilize a crowd-sourced labeling methodology. We collect third-party judgments about why searchers appear to struggle and, if appropriate, where in the search task it became clear to the judges that searches would succeed (i.e., the pivotal query). We use our findings to propose ways in which systems can help searchers reduce struggling. Key components of such support are algorithms that accurately predict the nature of future actions and their anticipated impact on search outcomes. Our findings have implications for the design of search systems that help searchers struggle less and succeed more.