Items by Kamvar, Maryam

We present a logs-based comparison of search patterns across three platforms: computers, iPhones and conventional mobile phones. Our goal is to understand how mobile search users differ from computer-based search users, and we focus heavily on the distribution and variability of tasks that users perform from each platform. The results suggest that search usage is much more focused for the average mobile user than for the average computer-based user. However, search behavior on high-end phones resembles computer-based search behavior more so than mobile search behavior. A wide variety of implications follow from these findings. First, there is no single search interface which is suitable for all mobile phones. We suggest that for the higher-end phones, a close integration with the standard computer-based interface (in terms of personalization and available feature set) would be beneficial for the user, since these phones seem to be treated as an extension of the users' computer. For all other phones, there is a huge opportunity for personalizing the search experience for the user's "mobile needs", as these users are likely to repeatedly search for a single type of information need on their phone.

We present a new CAPTCHA which is based on identifying an image’s upright orientation. This task requires analysis of the often complex contents of an image, a task which humans usually perform well and machines generally do not. Given a large repository of images, such as those from a web search result, we use a suite of automated orientation detectors to prune those images that can be automatically set upright easily. We then apply a social feedback mechanism to verify that the remaining images have a human-recognizable upright orientation. The main advantages of our CAPTCHA technique over the traditional text recognition techniques are that it is language-independent, does not require text-entry (e.g. for a mobile device), and employs another domain for CAPTCHA generation beyond character obfuscation. This CAPTCHA lends itself to rapid implementation and has an almost limitless supply of images. We conducted extensive experiments to measure the viability of this technique.