NDLI: Is Mail The Next Frontier In Search And Data Mining?

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Is Mail The Next Frontier In Search And Data Mining?

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Is Mail The Next Frontier In Search And Data Mining?

Content Provider	ACM Digital Library
Author	Maarek, Yoelle
Abstract	The nature of Web mail traffic has significantly evolved in the last two decades, and consequently the behavior of Web mail users has also changed. For instance a recent study conducted by Yahoo Labs showed that today 90% of Web mail traffic is machine-generated. This partly explains why email traffic continues to grow even if a significant amount of personal communications has moved towards social media. Most users today are receiving in their inbox important invoices, receipts, and travel itineraries, together with non-malicious junk mail such as hotel newsletters or shopping promotions that could safely ignore. This is one of the reasons that a majority of messages remain unread, and many are deleted without being read. In that sense, Web mail has become quite similar to traditional snail mail. In spite of this drastic change in nature, many mail features remain unchanged. While 70% of mail users do not define even a single folder, folders are still predominant in the left trail of many Web mail clients. Mail search results are still mostly ranked by date, which makes the retrieving of older messages extremely challenging. This is even more painful to users, as unlike in Web search, they will know when a relevant previously read message has not been returned. In this talk, I present the results of multiple large-scale studies that have been conducted at Yahoo Labs in the last few years. I highlight the inherent challenges associated with such studies, especially around privacy concerns. I will discuss the new nature of consumer Web mail, which is dominated by machine-generated messages of highly heterogeneous forms and value. I will show how the change has not been fully recognized yet by my most email clients. As an example, why should there still be a reply option associated with a message coming from a "do-not-reply@" address?. I will introduce some approaches for large-scale mail mining specifically tailored to machine-generated email. I will conclude by discussing possible applications and research directions.
Starting Page	203
Ending Page	203
Page Count	1
File Format	PDF
ISBN	9781450337168
DOI	10.1145/2835776.2835847
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-02-08
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Machine-generated email Mail search Web mail
Content Type	Text
Resource Type	Article

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