Venue Matching in Social Network APIs using Neural Networks
Published in:22nd ACM Panhellenic Conference on Informatics, ACM, Athens, Greece (2018)
Keywords:Machine Learning, POI matching, social networks
A multitude of social media APIs from popular services such as Facebook, Twitter and Google, allow programmers access to user generated data that is pertinent to physical venues represented within these services. In our paper, we attempt to address the issue of automatically matching venue representations from these diverse APIs, in order to obtain a more complete representation of user cyber-physical interaction with these venues. We present our work comparing a neural network approach against Nearest Point and Longest Common Substring algorithms.