87 citations · 200 across the 6 of their papers we have counts for
7 papers
Towards General-Purpose Representation Learning of Polygonal Geometries
Gengchen Mai, Chiyu Jiang, Weiwei Sun +6
Neural network representation learning for spatial data is a common need for geographic artificial intelligence (GeoAI) problems. In recent years, many advancements have been made…
Geographic Question Answering: Challenges, Uniqueness, Classification, and Future Directions
Gengchen Mai, Krzysztof Janowicz, Rui Zhu +2
As an important part of Artificial Intelligence (AI), Question Answering (QA) aims at generating answers to questions phrased in natural language. While there has been substantial…
SE-KGE: A Location-Aware Knowledge Graph Embedding Model for Geographic Question Answering and Spatial Semantic Lifting
Gengchen Mai, Krzysztof Janowicz, Ling Cai +5
Learning knowledge graph (KG) embeddings is an emerging technique for a variety of downstream tasks such as summarization, link prediction, information retrieval, and question answ…
Semantically-Enriched Search Engine for Geoportals: A Case Study with ArcGIS Online
Gengchen Mai, Krzysztof Janowicz, Sathya Prasad +5
Many geoportals such as ArcGIS Online are established with the goal of improving geospatial data reusability and achieving intelligent knowledge discovery. However, according to pr…
Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells
Gengchen Mai, Krzysztof Janowicz, Bo Yan +3
Unsupervised text encoding models have recently fueled substantial progress in NLP. The key idea is to use neural networks to convert words in texts to vector space representations…
TransGCN:Coupling Transformation Assumptions with Graph Convolutional Networks for Link Prediction
Ling Cai, Bo Yan, Gengchen Mai +2
Link prediction is an important and frequently studied task that contributes to an understanding of the structure of knowledge graphs (KGs) in statistical relational learning. Insp…