Contextual Feature Analysis to Improve Link Prediction for Location Based Social Networks

Date

2014-10-01

Author

Bayrak, Ahmet Engin
Polat, Faruk

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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In recent years, people started to communicate, interact, maintain relationship and share data (image, video, note, location, etc.) with their acquaintances through varying online social network sites. Online social networks with location and time sharing/interaction among people are called Location Based Social Networks (LBSNs). Link prediction in social networks aims at predicting future possible links for representing the real life relations better. In this work, we studied the link prediction problem and proposed new contextual features that improve the link prediction performance for LBSNs.

URI

https://hdl.handle.net/11511/69623

DOI

https://doi.org/10.1145/2659480.2659499

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Department of Computer Engineering, Conference / Seminar

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Citation Formats

A. E. Bayrak and F. Polat, “Contextual Feature Analysis to Improve Link Prediction for Location Based Social Networks,” 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/69623.