[PDF][PDF] Symbolic and subsymbolic GeoAI: Geospatial knowledge graphs and spatially explicit machine learning.
The field of Artificial Intelligence (AI) can be roughly divided into two branches: Symbolic
Artificial Intelligence and Connectionist Artificial Intelligence (or so-called Subsymbolic AI) …
Artificial Intelligence and Connectionist Artificial Intelligence (or so-called Subsymbolic AI) …
EVKG: An interlinked and interoperable electric vehicle knowledge graph for smart transportation system
Over the past decade, the electric vehicle (EV) industry has experienced unprecedented
growth and diversification, resulting in a complex ecosystem. To effectively manage this …
growth and diversification, resulting in a complex ecosystem. To effectively manage this …
A survey of deep learning and foundation models for time series forecasting
Deep Learning has been successfully applied to many application domains, yet its
advantages have been slow to emerge for time series forecasting. For example, in the well …
advantages have been slow to emerge for time series forecasting. For example, in the well …
Knowledge Enhanced Deep Learning: Application to Pandemic Prediction
Deep Learning has been successfully applied to many problem domains, yet its advantages
have been slow to emerge for time series forecasting. For example, in the well-known M …
have been slow to emerge for time series forecasting. For example, in the well-known M …
GeoAI Methodological Foundations: Deep Neural Networks and Knowledge Graphs
The chapter provides an overview of the methodological foundations of GeoAI, with a focus
on the use of deep learning and knowledge graphs. It covers a range of key concepts and …
on the use of deep learning and knowledge graphs. It covers a range of key concepts and …
[HTML][HTML] The cultural-social nucleus of an open community: A multi-level community knowledge graph and NASA application
RM McGranaghan, E Young, C Powers, S Yadav… - Applied Computing and …, 2023 - Elsevier
The challenges faced by science, engineering, and society are increasingly complex,
requiring broad, cross-disciplinary teams to contribute to collective knowledge, cooperation …
requiring broad, cross-disciplinary teams to contribute to collective knowledge, cooperation …
Fast Forward from Data to Insight:(Geographic) Knowledge Graphs and Their Applications
In this chapter, we explain what knowledge graphs are, how they relate to GeoAI research
such as knowledge engineering and representation learning, discuss their value proposition …
such as knowledge engineering and representation learning, discuss their value proposition …