We propose a framework for learning meaningful context embeddings for POIs, that incorporate domain knowledge and semantic information extracted from external�...
Aug 21, 2019 � ABSTRACT. State of the art works for Point-Of-Interest (POI) classification use either traditional feature extraction methods, or,�...
Learning Domain Driven and Semantically Enriched Embeddings for POI Classification. record by Giorgos Giannopoulos • Learning Domain Driven and Semantically�...
Learning domain driven and semantically enriched embeddings for poi classification. G Giannopoulos, M Meimaris. Proceedings of the 16th international symposium�...
This paper contributes a study of feature importance for the classification of unlabeled POIs into categories.
There are two main methods for POI data classification: those based on rich feature information and those based on finite element information. For the former�...
This paper proposes a multisource POI attribute alignment method based on the Enhanced Semantic Representation Model (ESRM).
A novel method that incorporates both onomastic and local contextual information in POI categorization is proposed that uses support vector machines (SVMs)�...
Feb 5, 2021 � In this paper, we extend the concept of semantic embedding for POIs (points of interests) and devise the first semantic embedding of ROIs.
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Giorgos Giannopoulos, Marios Meimaris: Learning Domain Driven and Semantically Enriched Embeddings for POI Classification. SSTD 2019; Giorgos Eftaxias�...