DyCon blog: Points of Interest Extraction and Prediction of Next Locations

DyCon blog: Points of Interest Extraction and Prediction of Next Locations

Spain. 10.03.2021. Aicha Karite recent member from our team, made a contribution to the DyCon Blog about “Points of Interest Extraction and Prediction of Next Locations“:

Generally, a prediction problem involves using past observations to predict or forecast one or more possible future observations. The goal is to guess about what might happen in the future. Knowing the future can impact our decisions today so we have a great interest in predicting it. In this project we tried first working on finding an algorithm that can help us define the points of interest of the users we have in the dataset. For that we implement an algorithm that can identify the users stop points.
Next step was predicting the next location of the users to do that we used different approaches (Markov chains, Random forest and Recurrent neural network).

KEYWORDS: GPS Trajectory; Clustering algorithm; Points of interests (POI); Prediction; Markov chain; Random Forest; DBSCAN; HDBSCAN.

Take a look the detailed explanation at DyCon Blog