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We present an algorithm to compute the expected value of location data from a user, without access to the specific coordinates of the location data point. We use decision-theoretic techniques to provide a principled way for a potential buyer to make purchasing decisions about private user location data. We illustrate our approach in three scenarios: the delivery of targeted ads specific to a user\u2019s home location, the estimation of traffic speed, and location prediction. In all three cases, the methodology leads to quantifiably better purchasing decisions than competing methods.<\/jats:p>","DOI":"10.1145\/3320431","type":"journal-article","created":{"date-parts":[[2019,9,12]],"date-time":"2019-09-12T14:22:21Z","timestamp":1568298141000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["To Buy or Not to Buy"],"prefix":"10.1145","volume":"5","author":[{"given":"Heba","family":"Aly","sequence":"first","affiliation":[{"name":"University of Maryland, College Park, MD, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John","family":"Krumm","sequence":"additional","affiliation":[{"name":"Microsoft Research, Redmond, WA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gireeja","family":"Ranade","sequence":"additional","affiliation":[{"name":"UC Berkeley, Berkeley, CA USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eric","family":"Horvitz","sequence":"additional","affiliation":[{"name":"Microsoft Research, Redmond, WA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2019,9,12]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Huberman","author":"Adar Eytan","year":"2001","unstructured":"Eytan Adar and Bernardo A . 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