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http://dx.doi.org/10.5762/KAIS.2020.21.3.407

Automatic Recommendation of Nearby Tourist Attractions related to Events  

Ahn, Jinhyun (Department of Management Information Systems, Jeju National University)
Im, Dong-Hyuk (Department of Computer Engineering, Hoseo University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.21, no.3, 2020 , pp. 407-413 More about this Journal
Abstract
Participating in exhibitions is one of the major activities for tourists. When selecting their next travel destination after participating in an event, they use map services and social network services, such as blogs, to obtain information about tourist attractions. The map services are location-based recommendations, because they can easily retrieve information regarding nearby places. Blogs contain informative content about tourist attractions, thereby providing content-based recommendations. However, few services consider both location and content. In location-based recommendations, tourist attractions that are not related to the content of the event attended might be recommended. Content-based recommendation has a disadvantage in that events located at a distance might get recommended. We propose an algorithm that considers both location and content, based on information from the Korea Tourism Organization's Linked Open Data (LOD), Wikipedia, and a Korean dictionary. By extracting nouns from the description of a tourist attraction and then comparing them with nouns about other attractions, a content-based relationship is determined. The distance to the event is calculated based on the latitude and longitude of each tourist attraction. A weight selected by the user is used for linear combination with the content-based relationship to determine the preference order of the recommendations.
Keywords
Tourist Attractions Recommendation; Location-based; Content-based; Ontology; RDF;
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