Scipediacontent: Scipediacontent moved page Draft Content 620834050 to Lorenzo et al 2010a

2021-01-28T17:32:32Z

Scipediacontent moved page Draft Content 620834050 to Lorenzo et al 2010a

Scipediacontent: Created page with " == Abstract == city offers thousands of social events a day, and it is difficult for dwellers to make choices. The combination of mobile phones and recommender systems can..."

2021-01-28T17:32:29Z

Created page with " == Abstract == city offers thousands of social events a day, and it is difficult for dwellers to make choices. The combination of mobile phones and recommender systems can..."

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== Abstract ==

city offers 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, recommender systems can now identify patterns in people’s movements in order to, for example, recommend events. To do so, the system relies on having mobile users who share their attendance at a large number of social events: cold-start users, who have no location history, cannot receive recommendations. We set out to address the mobile cold-start problem by answering the following research question: how can social events be recommended to a cold-start user based only on his home location? To answer this question, we carry out a study of the relationship between preferences for social events and geography, the first of its kind in a large metropolitan area. We sample location estimations of one million mobile phone users in Greater Boston, combine the sample with social events in the same area, and infer the social events attended by 2,519 residents. Upon this data, we test a variety of algorithms for recommending social events. We find 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.

== Original document ==

The different versions of the original document can be found in:

* [http://discovery.ucl.ac.uk/171458/1/171458.pdf http://discovery.ucl.ac.uk/171458/1/171458.pdf]

* [http://dx.doi.org/10.1109/icdm.2010.152 http://dx.doi.org/10.1109/icdm.2010.152]

* [http://ieeexplore.ieee.org/document/5694070 http://ieeexplore.ieee.org/document/5694070],
: [https://ieeexplore.ieee.org/document/5694070 https://ieeexplore.ieee.org/document/5694070],
: [http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.ieee-000005694070 http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.ieee-000005694070],
: [http://www0.cs.ucl.ac.uk/staff/N.Lathia/papers/recommending10quercia.pdf http://www0.cs.ucl.ac.uk/staff/N.Lathia/papers/recommending10quercia.pdf],
: [https://doi.org/10.1109/ICDM.2010.152 https://doi.org/10.1109/ICDM.2010.152],
: [https://academic.microsoft.com/#/detail/2106558516 https://academic.microsoft.com/#/detail/2106558516]

* [http://xplorestaging.ieee.org/ielx5/5690658/5693950/05694070.pdf?arnumber=5694070 http://xplorestaging.ieee.org/ielx5/5690658/5693950/05694070.pdf?arnumber=5694070],
: [http://dx.doi.org/10.1109/icdm.2010.152 http://dx.doi.org/10.1109/icdm.2010.152]

* [https://discovery.ucl.ac.uk/id/eprint/171458 https://discovery.ucl.ac.uk/id/eprint/171458],
: [https://discovery.ucl.ac.uk/id/eprint/171458/1/171458.pdf https://discovery.ucl.ac.uk/id/eprint/171458/1/171458.pdf]

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Lorenzo et al 2010a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 620834050 to Lorenzo et al 2010a

Scipediacontent: Created page with " == Abstract == city offers thousands of social events a day, and it is difficult for dwellers to make choices. The combination of mobile phones and recommender systems can..."