{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,30]],"date-time":"2025-12-30T08:45:09Z","timestamp":1767084309576,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":17,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,8,19]],"date-time":"2019-08-19T00:00:00Z","timestamp":1566172800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,8,19]]},"DOI":"10.1145\/3340964.3340992","type":"proceedings-article","created":{"date-parts":[[2019,8,16]],"date-time":"2019-08-16T19:51:28Z","timestamp":1565985088000},"page":"214-217","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Learning Domain Driven and Semantically Enriched Embeddings for POI Classification"],"prefix":"10.1145","author":[{"given":"Giorgos","family":"Giannopoulos","sequence":"first","affiliation":[{"name":"IMSI\/Athena Research Center, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marios","family":"Meimaris","sequence":"additional","affiliation":[{"name":"IMSI\/Athena Research Center, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2019,8,19]]},"reference":[{"key":"e_1_3_2_1_1_1","first-page":"1616","article-title":"A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications","volume":"30","author":"HongYun Cai","year":"2018","unstructured":"HongYun Cai , Vincent Wenchen Zheng, and Kevin Chen-Chuan Chang . 2018 . A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications . IEEE TKDE 30 (2018), 1616 -- 1637 . HongYun Cai, Vincent Wenchen Zheng, and Kevin Chen-Chuan Chang. 2018. A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications. IEEE TKDE 30 (2018), 1616--1637.","journal-title":"IEEE TKDE"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/WI-IAT.2014.78"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"crossref","unstructured":"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.","DOI":"10.18653\/v1\/E17-2016"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186131"},{"key":"e_1_3_2_1_5_1","unstructured":"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."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-34129-3_33"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/2666310.2666476"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/2792838.2796555"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"crossref","unstructured":"M. Kejriwal and P. Szekely. 2017. Neural Embeddings for Populated Geonames Locations. In ISWC. 139--146.  M. Kejriwal and P. Szekely. 2017. Neural Embeddings for Populated Geonames Locations. In ISWC. 139--146.","DOI":"10.1007\/978-3-319-68204-4_14"},{"key":"e_1_3_2_1_10_1","unstructured":"T. Mikolov I. Sutskever K. Chen G. Corrado and J. Dean. 2013. Distributed Representations of Words and Phrases and Their Compositionality. In NIPS.   T. Mikolov I. Sutskever K. Chen G. Corrado and J. Dean. 2013. Distributed Representations of Words and Phrases and Their Compositionality. In NIPS."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"crossref","unstructured":"Petar Ristoski and Heiko Paulheim. 2016. RDF2Vec: RDF Graph Embeddings for Data Mining. In ISWC.  Petar Ristoski and Heiko Paulheim. 2016. RDF2Vec: RDF Graph Embeddings for Data Mining. In ISWC.","DOI":"10.1007\/978-3-319-46523-4_30"},{"key":"e_1_3_2_1_12_1","unstructured":"D. Skoutas D. Sacharidis and K. Stamatoukos. 2016. Identifying and Describing Streets of Interest. In EDBT. 437--448.  D. Skoutas D. Sacharidis and K. Stamatoukos. 2016. Identifying and Describing Streets of Interest. In EDBT. 437--448."},{"key":"e_1_3_2_1_13_1","volume-title":"DLocRL: A Deep Learning Pipeline for Fine-Grained Location Recognition and Linking in Tweets. CoRR abs\/1901.07005","author":"Canwen X.","year":"2019","unstructured":"Canwen X. , Jing L. , Xiangyang L. , Jiaxin P. , Chenliang L. , and Dong-Hong J. 2019. DLocRL: A Deep Learning Pipeline for Fine-Grained Location Recognition and Linking in Tweets. CoRR abs\/1901.07005 ( 2019 ). Canwen X., Jing L., Xiangyang L., Jiaxin P., Chenliang L., and Dong-Hong J. 2019. DLocRL: A Deep Learning Pipeline for Fine-Grained Location Recognition and Linking in Tweets. CoRR abs\/1901.07005 (2019)."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3139958.3140054"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132918"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3041021.3054138"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"crossref","unstructured":"K. Ziegler O. Caelen M. Garchery M. Granitzer L. He-Guelton J. Jurgovsky PE Portier and S. Zwicklbauer. 2017. Injecting Semantic Background Knowledge into Neural Networks using Graph Embeddings. WETICE (2017) 200--205.  K. Ziegler O. Caelen M. Garchery M. Granitzer L. He-Guelton J. Jurgovsky PE Portier and S. Zwicklbauer. 2017. Injecting Semantic Background Knowledge into Neural Networks using Graph Embeddings. WETICE (2017) 200--205.","DOI":"10.1109\/WETICE.2017.36"}],"event":{"name":"SSTD '19: 16th International Symposium on Spatial and Temporal Databases","sponsor":["TU Wien TU Wien"],"location":"Vienna Austria","acronym":"SSTD '19"},"container-title":["Proceedings of the 16th International Symposium on Spatial and Temporal Databases"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3340964.3340992","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3340964.3340992","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:13:32Z","timestamp":1750202012000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3340964.3340992"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,8,19]]},"references-count":17,"alternative-id":["10.1145\/3340964.3340992","10.1145\/3340964"],"URL":"https:\/\/doi.org\/10.1145\/3340964.3340992","relation":{},"subject":[],"published":{"date-parts":[[2019,8,19]]},"assertion":[{"value":"2019-08-19","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}