Code
Our methods are implemented as open source python libraries, available at LinkGeoML’s GitHub page.
Publications
- Konstantinos Alexis, Vassilis Kaffes, Giorgos Giannopoulos: Boosting Toponym Interlinking by paying Attention to both Machine and Deep Learning. GeoRich@SIGMOD 2020
- Vassilis Kaffes, Giorgos Giannopoulos, Spiros Skliadopoulos: Determining the provenance of land parcel polygons via machine learning. SSDBM 2020
- Konstantinos Alexis, Vassilis Kaffes, Ilias Varkas, Andreas Syngros, Nontas Tsakonas, Giorgos Giannopoulos: Improving geocoding quality via learning to integrate multiple geocoders. SSDBM 2020
- Giorgos Giannopoulos, Vassilis Kaffes, Georgios Kostoulas: Learning Advanced Similarities and Training Features for Toponym Interlinking. ECIR 2020
- Vassilis Kaffes, Giorgos Giannopoulos, Nikos Karagiannakis, Nontas Tsakonas: Learning Domain Specific Models for Toponym Interlinking. SIGSPATIAL/GIS 2019
- Giorgos Giannopoulos, Konstantinos Alexis, Nikos Kostagiolas, Dimitrios Skoutas: Classifying points of interest with minimum metadata. LocalRec@SIGSPATIAL 2019
- Giorgos Giannopoulos, Marios Meimaris: Learning Domain Driven and Semantically Enriched Embeddings for POI Classification. SSTD 2019
- Giorgos Eftaxias, Nontas Tsakonas, Giorgos Giannopoulos, Nikos Kostagiolas, Andreas Syngros, Dimitrios Skoutas: LGM-PC: A tool for POI classification on QGIS. SSTD 2019
Deliverables
Available only in Greek:
- D1.1: Use cases, KPIs and evaluation datasets.
- D1.2: Specification of training features.
- D2.1: Machine learning algorithm for spatio-textual data integration.
- D3.1: Feature selection methods spatio-textual data integration.