Learning Domain Driven and Semantically Enriched Embeddings for POI Classification-Reference-Cited by-同舟云学术

Learning Domain Driven and Semantically Enriched Embeddings for POI Classification

Published:2019-08-19 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 16th International Symposium on Spatial and Temporal Databases
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Author:

Giannopoulos Giorgos¹,Meimaris Marios¹

Affiliation:

1. IMSI/Athena Research Center, Greece

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3340964.3340992

Reference17 articles.

1. A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications;Cai HongYun;IEEE TKDE,2018

2. SJ Choi HJ Song SB Park and SJ Lee. 2014. A POI Categorization by Composition of Onomastic and Contextual Information. In WI-IAT. 38--45. 10.1109/WI-IAT.2014.78 SJ Choi HJ Song SB Park and SJ Lee. 2014. A POI Categorization by Composition of Onomastic and Contextual Information. In WI-IAT. 38--45. 10.1109/WI-IAT.2014.78

3. A. Cocos and C. Callison-Burch. 2017. The Language of Place: Semantic Value from Geospatial Context. In EACL. 99--104. A. Cocos and C. Callison-Burch. 2017. The Language of Place: Semantic Value from Geospatial Context. In EACL. 99--104.

4. D. Ding M. Zhang X. Pan D. Wu and P. Pu. 2018. Geographical Feature Extraction for Entities in Location-based Social Networks. In WWW. 833--842. 10.1145/3178876.3186131 D. Ding M. Zhang X. Pan D. Wu and P. Pu. 2018. Geographical Feature Extraction for Entities in Location-based Social Networks. In WWW. 833--842. 10.1145/3178876.3186131

5. M. Ester HP. Kriegel J. Sander and X. Xu. 1996. A Density-based Algorithm for Discovering Clusters a Density-based Algorithm for Discovering Clusters in Large Spatial Databases with Noise. In KDD. 226--231. M. Ester HP. Kriegel J. Sander and X. Xu. 1996. A Density-based Algorithm for Discovering Clusters a Density-based Algorithm for Discovering Clusters in Large Spatial Databases with Noise. In KDD. 226--231.

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