TribeFlow: Mining & Predicting User Trajectories

November 03, 2015 ยท Declared Dead ยท ๐Ÿ› The Web Conference

๐Ÿ‘ป CAUSE OF DEATH: Ghosted
No code link whatsoever

"No code URL or promise found in abstract"

Evidence collected by the PWNC Scanner

Authors Flavio Figueiredo, Bruno Ribeiro, Jussara Almeida, Christos Faloutsos arXiv ID 1511.01032 Category cs.SI: Social & Info Networks Cross-listed physics.data-an, physics.soc-ph, stat.ML Citations 51 Venue The Web Conference Last Checked 3 months ago
Abstract
Which song will Smith listen to next? Which restaurant will Alice go to tomorrow? Which product will John click next? These applications have in common the prediction of user trajectories that are in a constant state of flux over a hidden network (e.g. website links, geographic location). What users are doing now may be unrelated to what they will be doing in an hour from now. Mindful of these challenges we propose TribeFlow, a method designed to cope with the complex challenges of learning personalized predictive models of non-stationary, transient, and time-heterogeneous user trajectories. TribeFlow is a general method that can perform next product recommendation, next song recommendation, next location prediction, and general arbitrary-length user trajectory prediction without domain-specific knowledge. TribeFlow is more accurate and up to 413x faster than top competitors.
Community shame:
Not yet rated
Community Contributions

Found the code? Know the venue? Think something is wrong? Let us know!

๐Ÿ“œ Similar Papers

In the same crypt โ€” Social & Info Networks

Died the same way โ€” ๐Ÿ‘ป Ghosted