Fig. 1. Matching result of CNS POI (left) and Web POI(right) (Kim et al., 2009)
Fig. 2. Architecture of CBOW and Skip-gram model(Mikolov et al., 2013a)
Fig. 3. Illustration of the Word2Vec Skip-gram model learning
Fig. 4. Flowchart of POI search and alias database management algorithm
Fig. 5. Number of correct matches of POI search results through word embedding and similarity measurement according to the number of experiments
Fig. 6. Match rates of POI results according to numbers of experiment
Fig. 7. Validate alias database usability by attribute
Table 1. Four attributes of POI alias
Table 2. Mean and standard deviation of Similarity Measures, according to attributes
Table 3. Pseudocode for POI searches and alias databases management
참고문헌
- Elman, J.L. (1991), Distributed representations, simple recurrent networks, and grammatical structure, Machine Learning, Vol. 7, No. 2-3, pp. 195-225. https://doi.org/10.1007/BF00114844
- Glenberg, A.M. and Robertson, D.A. (2000), Symbol grounding and meaning: a comparison of high-dimensional and embodied theories of meaning, Journal Of Memory And Language, Vol. 43, No. 3, pp. 379-401. https://doi.org/10.1006/jmla.2000.2714
- Gomaa, W.H. and Fahmy, A.A. (2013), A survey of text similarity approaches, International Journal of Computer Applications, Vol. 68, No. 13, pp. 13-18. https://doi.org/10.5120/11638-7118
- Google. (2013), Word2vec, https://code.google.com/archive/p/word2vec/ (last date accessed : 14 January 2019).
- Harris, Z.S. (1954), Distributional structure. Word, Vol. 10, No. 2-3, pp. 146-162. https://doi.org/10.1080/00437956.1954.11659520
- Kim, J.O., Huh, Y., Lee, W.H. and Yu, K.Y. (2009), Matching method of digital map and POI for geospatial web platform, Journal of Korean Society for Geospatial Information System, Vol. 17, No. 4, pp. 23-29.
- Ko, E.B. and Lee, J.W. (2013), Implementation of a set-based POI search algorithm supporting classifying duplicate characters, Journal of Digital Contents Society, Vol. 14, No. 4, pp. 463-469. (in Korean with English abstract) https://doi.org/10.9728/dcs.2013.14.4.463
- Lee, J. (2009), GIS-based geocoding methods for area-based addresses and 3D addresses in urban areas, Environment and Planning B: Planning and Design, Vol. 36, No. 1, pp. 86-106. https://doi.org/10.1068/b31169
- Mikolov, T., Chen, K., Corrado, G., and Dean, J. (2013a), Efficient estimation of word representations in vector space, arXiv preprint arXiv:, pp. 1301.3781.
- Mikolov, T., Sutskever, I., Chen, K., Corrado, G.S., and Dean, J. (2013b), Distributed representations of words and phrases and their compositionality, In Advances In Neural Information Processing Systems , pp. 3111-3119.
- OGC(Open Geospatial Concortium). (2013), Points of interest (POI) Standards Working Group Charter, https://portal.opengeospatial.org/files/?artifact_id=54800 (last date accessed : 12 April 2019).
- Park, J.H., Kang, H.Y., and Lee, J. (2016), A spatial-temporal POI data model for implementing location-based services, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 34, No. 6, pp. 609-618. https://doi.org/10.7848/ksgpc.2016.34.6.609
- Ratcliff, J.W. and Metzener, D.E. (1988), Pattern-matchingthe gestalt approach, Dr Dobbs Journal, Vol. 13, No. 7, pp. 46.
- Sasaki, Y., Ishikawa, Y., Fujiwara, Y., and Onizuka, M. (2018), Sequenced Route Query with Semantic Heirarchy. Proceedings of the 21st International Conference on Extending Database Techology, 26-29 March 2019, Lisbon, Portugal, pp. 37-48.
- TTA. (2014), POI (Point of Interest) data model, http://www.tta.or.kr/data/ttas_view.jsp?r n=1&by=desc&r n1=Y&standard_no=TTAK.OT-10.0360&order=publish_date&publish_date=%C2%A7ion_code%3D&nowpage=1&totalSu=1&pk_num=TTAK.OT-10.0360&nowSu=1 (last date accessed : 12 April 2019).
- Xu, C., Li, Q., and Yong, W. (2012), The Design and Implementation of Address Matching Engine. Proceedings of the International Conference on Geo-spatial Solutions for Emergency Management an the 50 th Anniversary of Chinese Academy of Surveying and Mapping, 14-16 September 2009, Beijing, China. ISPRS Archives Volume XXXVIII-7/C4, pp. 118-120.
피인용 문헌
- Improving a Street-Based Geocoding Algorithm Using Machine Learning Techniques vol.10, pp.16, 2019, https://doi.org/10.3390/app10165628