Weighted Machine Learning for Spatial-Temporal Data

Machine Learning Models for Housing Prices Forecasting using Registration Data

This article has been compiled to identify the best model of housing price forecasting using machine learning methods with maximum accuracy and minimum error. Five important machine learning algorithms are used to predict housing prices, including Nearest Neighbor Regression Algorithm (KNNR), Support Vector Regression Algorithm (SVR), Random Forest Regression Algorithm (RFR), Extreme Gradient B...

Machine Learning Paradigms for Modeling Spatial and Temporal Information in Multimedia Data Mining

Multimedia data mining and knowledge discovery is a fast emerging interdisciplinary applied research area. There is tremendous potential for effective use of multimedia data mining (MDM) through intelligent analysis. Diverse application areas are increasingly relying on multimedia understanding systems. Advances in multimedia understanding are related directly to advances in signal processing, ...

Structured and Unstructured Machine Learning for Crowdsourced Spatial Data

Recent years have seen a significant increase in the number of applications requiring accurate and up-to-date spatial data. In this context crowdsourced maps such as OpenStreetMap (OSM) have the potential to provide a free and timely representation of our world. However, one factor that negatively influences the proliferation of these maps is the uncertainty about their data quality. This paper...

Local Machine Learning Models for Spatial Data Analysis

Gesture Unit Segmentation Using Spatial-Temporal Information and Machine Learning

Currently, automated gesture analysis is being widely used in different research areas, such as humancomputer interaction or human-behavior analysis. With regard to the latter area in particular, gesture analysis is closely related to studies on human communication. Linguists and psycholinguists analyze gestures from several standpoints, and one of them is the analysis of gesture segments. The ...