Global budgets for local recommendations.

ABSTRACTWe present the design, implementation and evaluation of a new geotagging service, Gloe, that makes it easy to find, rate and recommend arbitrary on-line content in a mobile setting. The service automates the content search process by taking advantage of geographic and social context, while using crowdsourced expertise to present a personalized feed of targeted information ranked by a novel geo-aware rating and incentive mechanism. Users rate the relevance of recommendations for particular locations using a limited, global voting budget. This budget is, in turn, increased by accurately predicting local content popularity. One of the key goals of our mechanism is to encourage ratings, and in an evaluation of the live system we found that the rating to click ratio was 107 times higher than the ratio for videos on YouTube, 34 times higher than the ratio for applications on the Android Market, and 3 times higher than the ratio for Web pages on Digg. To investigate whether our mechanism also had qualitative effects on the ratings we conducted a number of experiments on Amazon Mechanical Turk, with 500 users, comparing our mechanism to the de-facto 5-star ratings commonly in use on the Web. Our results show that budgets improved the ranking and incentives improved the aggregate rating of a series of location-dependent Web pages.