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As a real estate search engine, Trulia encounters a great deal of geo-coded and locale specific data, not just about the properties themselves but also conditions and contexts guiding a home purchasing decision. Some of this data is standardized or factual, but a great deal is subjective and difficult to quantify and integrate into a coherent data set. We’ll discuss Trulia’s approach to Geodata and how we use it to derive economic meaning, and ultimately, value for users from this data that isn’t available from traditional sources. We’ll also discuss how to integrate user contributed and Trulia accumulated data to identify emerging trends and patterns before this data is available from traditional sources.
Jesper develops experimental online services designed to introduce emotional contexts into online relationships, creating more authentic experiences. He is the co-founder of Bloom Studios, developing novel data interface applications for web and tablet platforms. He is also an accomplished data scientist, working on problems including home valuations for Trulia, credit card fraud for Visa, and social network analysis for Visible Path. Jesper speaks frequently at international technology and design conferences and has appeared in print and broadcast media for projects like Avoidr, Freerisk, and his Foursquare privacy hack. He holds a B.Sc. in Physics from Haverford College and an M.B.A. in Econometrics from University of Chicago.