University of Cambridge > Talks.cam > Computer Laboratory Systems Research Group Seminar > Recommending Social Events from Mobile Phone Location Data

Recommending Social Events from Mobile Phone Location Data

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Cities offer thousands of social events a day, and it is difficult for dwellers to make choices. The combination of mobile phones and recommender systems can change the way one deals with such abundance. Mobile phones with positioning technology are now widely available, making it easy for people to broadcast their whereabouts and recommender systems can now identify patterns in people’s movements. We have carried out a study of the relationship between preferences for social events and geography, the first of its kind in a large metropolitan area. We have sampled location estimations of one million mobile phone users in Greater Boston, combined the sample with social events in the same area, and inferred the social events attended by 2,519 residents. Upon this data, we have tested a variety of algorithms for recommending social events. We found that the most effective algorithm recommends events that are popular among residents of an area. The least effective, instead, recommends events that are geographically close to the area. This last result has interesting implications for location-based services that emphasize recommending nearby events.

blog post: http://tinyurl.com/36zjb88

paper: http://tinyurl.com/32u2dpe

This talk is part of the Computer Laboratory Systems Research Group Seminar series.

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