Dwipa Ontology III: Implementation of Ontology Method Enrichment on Tourism Domain


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International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

Exeley Inc. (New York)

Subject: Computational Science & Engineering, Engineering, Electrical & Electronic


eISSN: 1178-5608



VOLUME 10 , ISSUE 4 (December 2017) > List of articles

Dwipa Ontology III: Implementation of Ontology Method Enrichment on Tourism Domain

Guson Prasamuarso Kuntarto * / Irwan Prasetya Gunawan * / Fahmi L. Moechtar * / Yudhiansyah Ahmadin * / Berkah I. Santoso *

Keywords : Ontology Enrichment, machine learning, statistics, linguistics, tourism domain, semi-automatic, Ontology Dwipa III

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 10, Issue 4, Pages 903-919, DOI: https://doi.org/10.21307/ijssis-2018-024

License : (BY-NC-ND 4.0)

Received Date : 05-August-2017 / Accepted: 12-November-2017 / Published Online: 01-December-2017



This article summarizes some research results related to ontology enrichment specific to tourism domains from 2014 to 2017. Currently, some ontology enrichment approaches can use learning machinery such as support vector machine (SVM), Conditional Random Field (CRF) and kNN. Several studies have also been successful in evaluating ontology enrichment results with several parameters such as precision, recall and F-Measure. In addition, our research can enrich Dwipa Ontology II which has been successfully done by population to object / sample. The method used in this research is ontology enrichment method. This technique or method is used to show background knowledge (ontology) by adding new concepts and relationships through the extraction process. The enrichment process is done on semi-automated web document (corpus). The process using statistics and linguistics, by applying evaluation techniques by using reviewers in the field of tourism. The end result of Dwipa Ontology III (enriched ontology) contains 4 main classes, 15 subclasses and 199 samples / objects. The expansion of general concept / subclass knowledge under the attraction classes are: cultural parks, artists and monuments.

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[1] Andriani, D. (2014). Kontribusi ke Negara Besar, Pariwisata Layak jadi Sektor Unggulan. Retrieved April 23, 2106 from http://industri.bisnis.com/read/20140226/12/206310/kontribusi-ke-negara-besar-pariwisata-layak-jadisektor-unggulan.
[2] Bacciu C., A, Duca, L. A., Marchetti, A. , & Tesconi, M. (2014). Accommodations in Tuscany as Linked Data. Proceedings of The 9th edition of the Language Resources and Evaluation Conference (LREC), Reykjavik, Iceland.
[3] Banowosari L., T., Simri I., W., Wirawan S., & Dewi J. T. (2012). “Memperkaya Instances pada Ontology Pariwisata dengan Sumber dari Internet” Konferensi Nasional Sistem Informasi (KNSI), pp. 214,219, 23-25 Feb. 2012.
[4] Barforush, A. A., & Rahnama, A. (2012). Ontology learning: revisted. Journal of Web Engineering, 11(4), 269-289.
[5] Castano, S., Espinosa, S., Ferrara, A., Karkaletsis, V., Kaya, A., Melzer, S., ... & Petasis, G. (2007, June). Ontology dynamics with multimedia information: The boemie evolution methodology. In International Workshop on Ontology Dynamics (IWOD-07) (p. 41). G.P. Kuntarto, I.P. Gunawan, F.L. Moechtar, Y. Ahmadin, B.I. Santoso, DWIPA ONTOLOGY III IMPLEMENTATION OF ONTOLOGY METHOD ENRICHMENT ON TOURISM DOMAIN
[6] Dennai, A. & Benslimane, S. M. (2015). Semantic Indexing of Web Documents Based on Domain Ontology. I.J. Information Technology and Computer Science, 2015, 02, 1(11). DOI: 10.5815/ijitcs.2015.02.01.
[7] Imsombut, A. & Kajornrit, J. (2017). Comparing Statistical and Data Mining Techniques for Enrichment Ontology with Instances. Journal of Reviews on Global Economics, 2017, vol. 6, 375-379
[8] Kularbphettong, K. (2017). Enrichment Ontology Instance by Using Data Mining Techniques. In Proceedings CoMeSySo 2017: Applied Computational Intelligence and Mathematical Methods pp 150-155.
[9] Kuntarto, G.P. & Gunawan, D. (2012). "Dwipa search engine: When E-tourism meets the semantic web," International Conference on Advanced Computer Science and Information Systems (ICACSIS), pp.155,160, 1-2 Dec. 2012.
[10] Kuntarto, G. P., Moechtar, F. L., Santoso, B. I., & Gunawan, I. P. (2015, November). Comparative study between Part-of-Speech and statistical methods of text extraction in the tourism domain. In 2015 International Conference on Information Technology Systems and Innovation (ICITSI) (pp. 1-6). IEEE.
[11] Lisi, F. A. & Esposito, F. (2014). Semantic Web Services for Integrated Tourism in the Apulia Region. In L.Giordano, V. Gliozzi & G. L. Pozzato (eds.), CILC (p./pp. 178-193), : CEUR-WS.org.
[12] Maedche, A., & Staab, S. (2002). Applying semantic web technologies for tourism information systems. na.
[13] Medeiros C. (2008). Ontology Learning [PowerPoint slides]. Retrieved April 20, 2016 from www.cin.ufpe.br/~in1099/082/slides-ontolearning.pdf
[14] Petasis, G., Karkaletsis, V., Paliouras, G., Krithara, A., & Zavitsanos, E. (2011, January). Ontology population and enrichment: State of the art. In Knowledge-driven multimedia information extraction and ontology evolution (pp. 134-166). Springer-Verlag.
[15] Ruiz-Martınez, J. M., Minarro-Giménez, J. A., Castellanos-Nieves, D., Garcıa-Sánchez, F., & Valencia-Garcia, R. (2011). Ontology population: an application for the E-tourism domain. International Journal of Innovative Computing, Information and Control (IJICIC), Vol. 7(11), 6115-6134.
[16] Soualah-Alila, Fayrouz and Coustaty, Mickael and Rempulski, Nicolas and Doucet, Antoine. (2016). DataTourism : Designing an Architecture to Process Tourism Data. Information and Communication Technologies in Tourism 2016. p. 751-763. Springer
[17] Tachapetpaiboon, N. & Kularbphettong, K. (2015). Ontology Based Knowledge Management for Cultural Tourism. Journal of Theoretical and Applied Information Technology. Vol. 75(3). E-ISSN: 1817-3195.
[18] Tanaamah, A., D. & Wellem, T. (2009). Semantik Web sebagai solusi Pemecahan Masalah Promosi Kepariwisataan di Indonesia. Jurnal Teknologi Informasi (AITI), 6(2), 101-200. Retrieved April 20, 2016 from http://ris.uksw.edu/download/jurnal/kode/J00003.
[19] T. Berners-Lee, J. Hendler and O. Lassila. (2001). The semantic web, Scientific American Magazine, vol.284, pp.34-43.
[20] Winaga R. (2013). Basis Pengetahuan pariwisata berbasis ontologi yang memodelkan waktu valid. [Abstract] Thesis Abstract. Retrieved January 15, 2016 from http://www.digilib.ui.ac.id/opac/themes/libri2/detail.jsp?id=20330287&lokasi=lokal.
[21] Vanjulavalli N. & Kovalan A. (2012). Ontology Based Semantic Search Engine. International Journal of Computer Science Engineering and Technology (IJCET), Vol. 2(8), pp. 1349-1353, ISSN: 2331-0711, Retrieved April 10, 2016 from: http://www.ijcset.net/docs/Volumes/volume2issue8/ijcset2012020803.pdf.
[22] Kuntarto, G. P., Moechtar, F. L., Santoso, B. I., Gunawan, I. P., & Ahmadin Y. (2017, November). Dwipa Ontology II: Semi-Automatic Ontology Population for Bali Tourism based on the Ontology Population Methodology. In 2017 International Conference on Smart Cities, Automation & Intelligent Computing System (ICON-SONICS 2017). IEEE.
[23] Zhang F, Liu W, and Bi Y. (2013). Review On WordNet-Based Ontology Construction in China. In International Journal on Smart Sensing and Intelligent Systems (S2IS). Vol. 6(2). ISSN: 1178-5608.