你真的需要多少个？
How Many Folders Do You Really Need?
摘要：
电子邮件分类仍然是一项主要的手动任务。因此，大多数Web邮件用户从不定义单个文件夹。然而，最近，自动分类提供相同的类别给所有用户已经开始出现在一些Web邮件客户端，如AOL或Gmail。我们采用这种方法，而不是以前的（不成功的）个性化的方法，因为消费者电子邮件流量的性质的变化，这是现在占主导地位的（非垃圾邮件）机器生成的电子邮件。我们在这里提出了一种新的方法（1）自动区分个人和机器生成的电子邮件和（2）分类到潜在类别的消息，而不需要用户定义任何文件夹。我们报告了我们如何发现一组6个“潜在”类别（一个用于人类，另一个用于机器生成的消息）可以解释电子邮件流量的重要部分。我们详细描述了建立一个Web规模的电子邮件分类系统所涉及的步骤，从地面实况标签的收集，功能的选择，模型的训练。对雅虎邮件服务用户在六个月内收到的5000多亿条信息进行了实验性评估，这些用户选择参加这种研究。我们的系统实现了接近90%的准确率和召回率，我们发现的潜在类别覆盖了70%的电子邮件流量和电子邮件搜索查询。我们相信，这些结果铺平了道路，在Web邮件行业的方法的变化，并可以支持新的大规模电子邮件发现范例，以前没有可能的发明。
英文摘要：
Email classification is still a mostly manual task. Consequently, most Web mail users never define a single folder. Recently however, automatic classification offering the same categories to all users has started to appear in some Web mail clients, such as AOL or Gmail. We adopt this approach, rather than previous (unsuccessful) personalized approaches because of the change in the nature of consumer email traffic, which is now dominated by (non-spam) machine-generated email. We propose here a novel approach for (1) automatically distinguishing between personal and machine-generated email and (2) classifying messages into latent categories, without requiring users to have defined any folder. We report how we have discovered that a set of 6 "latent" categories (one for human- and the others for machine-generated messages) can explain a significant portion of email traffic. We describe in details the steps involved in building a Web-scale email categorization system, from the collection of ground-truth labels, the selection of features to the training of models. Experimental evaluation was performed on more than 500 billion messages received during a period of six months by users of Yahoo mail service, who elected to be part of such research studies. Our system achieved precision and recall rates close to 90% and the latent categories we discovered were shown to cover 70% of both email traffic and email search queries. We believe that these results pave the way for a change of approach in the Web mail industry, and could support the invention of new large-scale email discovery paradigms that had not been possible before.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
