• Title/Summary/Keyword: 관광추천 시스템

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Tourist Attraction Recommendation System using Data Mining on Android (안드로이드에서 데이터 마이닝을 이용한 관광 명소 추천 시스템)

  • Kim, Sun-Ho;Park, Kyu-Tae;Kim, Young-A;Park, Doo-Soon
    • Proceedings of the Korea Information Processing Society Conference
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    • 2012.11a
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    • pp.1767-1769
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    • 2012
  • 최근 여가활동에 대한 관심이 증대되고 있으며, 모바일 인프라가 널리 보급되었다. 하지만 공유되는 정보의 양이 급속하게 증가함에 따라 원하는 정보를 정확하게 얻는 것은 쉽지 않다. 본 논문은 한국관광공사의 Open API를 이용하여 보다 객관적이고 정확한 관광 명소의 정보를 안드로이드 폰에서 볼 수 있도록 제공하고, 더불어 사용자의 취향에 알맞은 관광 명소를 추천해주는 시스템을 소개한다.

Cross-Domain Recommendation System in Complete Cold Start Problem (완전한 콜드 스타트 문제에서 교차 도메인 추천 시스템)

  • Nam, Gyuhyeon;You, Jaeseong;Chae, Gyeongsu
    • Annual Conference on Human and Language Technology
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    • 2019.10a
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    • pp.514-518
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    • 2019
  • 기존의 교차 도메인 추천은 일반적으로 서로 다른 도메인 데이터의 지식 결합이나 지식 공유를 바탕으로 진행된다. 이러한 방식들은 최소 한 개 이상의 도메인 데이터가 필요해서 모든 도메인의 피드백 데이터가 없는 실제 서비스 초기 상황에는 적합하지 않을 수 있다. 따라서 본 논문에서는 서비스 초반 모든 도메인의 피드백 데이터가 없고 콘텐츠 데이터만 존재하는 상황에서 교차 도메인 추천 시스템을 효과적으로 시작하기 위해 텍스트 임베딩, 클러스터링, 프로파일링 및 콘텐츠 기반 필터링을 활용한 추천 시스템 구성을 제안하고자 한다. 평가를 위해 여행지, 지역 축제, 공연을 포함하는 문화 관광 데이터와, 이에 대한 사용자 프로파일링 결과를 바탕으로 추천을 진행하였다. 그 결과, 콘텐츠 임베딩에 대한 유사도를 시각화하여 교차 도메인 아이템 간 유사성을 확인할 수 있었고, 사용자별 추천 결과를 통해 제안한 교차 도메인 추천 시스템이 유의미하게 동작함을 보였다.

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Image-based Tourism Recommender System (이미지 기반 여행지 추천 시스템)

  • Young-Min Na;Sol Kim;Gi-Yeon Song;Geumsang Lee;Jaehwan Lee
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.11a
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    • pp.396-397
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    • 2023
  • 추천 시스템은 빅데이터 관련 기술과 알고리즘의 발달로 다양한 분야에서 사용되고 있다. 관광 산업도 예외는 아니다. 본 연구에서는 사용자들이 촬영한 사진을 기반으로 유사한 여행지를 추천하는 추천 시스템을 제안한다. 사용자가 입력한 이미지에서 언어적 특성과 비언어적 특성을 추출하고 이를 기반으로 유사한 이미지를 탐색하고, 이를 기반으로 사용자가 좋아할 다음 여행지를 추천한다. 사용자가 질의어를 입력하지 않고 이미지를 제공하여 추천이 이루어진다는 점과 사용자의실제 여행 여부를 이용해 모델의 성능을 평가했다는 점에서 연구의 의의가 있다.

Associative Classification based Customized Tourist Attraction Recommendation System applying CPFP-tree (CPFP-tree를 적용한 연관분류 기반의 사용자 맞춤형 관광명소 추천 시스템)

  • Kim, Hyeong-Soo;Park, Soo-Ho;Lee, Dong-Gyu;Ryu, Keun-Ho
    • Proceedings of the Korean Information Science Society Conference
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    • 2012.06c
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    • pp.134-136
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    • 2012
  • u-City 환경에서 사용자 맞춤형 국토정보를 제공하기 위해 대용량의 데이터를 효과적으로 분석할 수 있는 데이터마이닝 기법이 적용되고 있다. 따라서 이 논문에서는 데이터마이닝 기법 중 연관분류기법을 적용하여 사용자 맞춤형 관광명소 추천 시스템을 개발하였다. 특히, CPFP-tree를 이용하여 빈발항목집합 탐사에 대한 시간을 단축하였으며, 연관분류를 통해 보다 높은 정확도로 결과를 예측 및 분류할 수 있게 하였다. 제시한 시스템은 공간정보에 대해 사용자 맞춤 서비스를 제공할 수 있음을 보였으며, 다양한 시나리오 적용을 통해 맞춤형 국토정보화 기술의 기반이 될 수 있다.

스마트 요트운용시스템을 위한 추천관광 항로 개발에 관한 연구

  • Gang, Nam-Seon
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2013.06a
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    • pp.10-11
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    • 2013
  • 최근 여가 관광의 기능이 활성화되고 해양활동에 대한 관심이 증가하면서 주로 어업의 대상으로 여겨지던 해양공간이 관광자원으로서의 중요성이 부각되고 있으며, 여가활동 및 가족단위 관광활동의 증가로 인하여 해양환광활동에 대한 국민적 관심이 높아지면서 해양레저에 대한 수요가 증가하고 있다. 하지만 우리나라 해양레저활동의 현실은 시설 및 프로그램이 활성화되지 못하고 있으며, 기존의 낚시나 유선사업의 수준을 벗어나지 못하고 있다. 현재 해양레저활동자 조차도 바다에 관한 깊은 이해와 일정수준의 기술 및 노하우를 가지지 못한 상황이며, 레저보트가 접근할 수 있는 지역의 정보 부족으로 근거리의 단순한 경로만을 반복적으로 운항하고 있는 실정이다. 따라서 본 연구에서는 이러한 문제점을 개선하고 요트항해에 필요한 다양한 정보의 제공에 대응하여 해양레저활동을 위한 레저항로를 부산지역을 중심으로 제안하였다.

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A Development of Navigation Routes Recommendation System with Elements Analysis of Marine Leisure Activities (해양 레저 활동을 위한 요소 분석 및 항로 추천 시스템의 개발)

  • Kim, Bae-Sung;Hwang, Hun-Gyu;Shin, Il-Sik;Lee, Jang-Se;Yoo, Yung-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.7
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    • pp.1355-1362
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    • 2016
  • Recently, the marine leisure are being emphasized with improving the quality of life style by increased income and spare time. Also, there is a increasement of people's interest in marine leisure activities. But resources and facilities do not grow in proportion to the quantitative growth of the current marine leisure industry. Besides, a leisure ship operator tends to choose a simple or familiar route of the local area rather than a new leisure routes which are not explored due to lack of accessible areas information. This paper proposes a routes recommendation system in order to solve above problems based on marine resource database. The databases have been constructed through investigation and analysis of navigational information such as environmental conditions including weather conditions and sea status, field of marine leisure activities, tourist attractions and natural landscape, and marine leisure prohibited areas. Therefore we have developed and implemented the route recommendation system that provides various information necessary to route operation of leisure boats.

Analyzing TripAdvisor application reviews to enable smart tourism : focusing on topic modeling (스마트 관광 활성화를 위한 트립어드바이저 애플리케이션 리뷰 분석 : 토픽 모델링을 중심으로)

  • YuNa Lee;MuMoungCho Han;SeonYeong Yu;MeeQi Siow;Mijin Noh;YangSok Kim
    • Smart Media Journal
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    • v.12 no.8
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    • pp.9-17
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    • 2023
  • The development of information and communication technology and the improvement of the development and dissemination of smart devices have caused changes in the form of tourism, and the concept of smart tourism has since emerged. In this regard, researches related to smart tourism has been conducted in various fields such as policy implementation and surveys, but there is a lack of research on application reviews. This study collects Trip Advisor application review data in the Google Play Store to identify usage of the application and user satisfaction through Latent Dirichlet Allocation (LDA) topic modeling. The analysis results in four topics, two of which are positive and the other two are negative. We found that users were satisfied with the application's recommendation system, but were dissatisfied when the filters they set during search were not applied or that reviews were not published after updates of the application. We suggest more categories can be added to the application to provide users with different experiences. In addition, it is expected that user satisfaction can be improved by identifying problems within the application, including the filter function, and checking the application environment and resolving the error occurring during the application usage.

Nearest Neighbor Query Processing using the Direction of Mobile Object (모바일 객체의 방향성을 고려한 최근접 질의 처리)

  • Lee, Eung-Jae;Jung, Young-Jin;Choi, Hyon-Mi;Ryu, Keun-Ho;Lee, Seong-Ho
    • Journal of Korea Spatial Information System Society
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    • v.6 no.1 s.11
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    • pp.59-71
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    • 2004
  • Nearest neighbor query retrieves nearest located target objects, and is very frequently used in mobile environment. In this paper we propose a novel neatest neighbor query processing technique that is able to retrieve nearest located target object from the user who is continuously moving with a direction. The proposed method retrieves objects using the direction property of moving object as well as euclidean distance to target object. The proposed method is applicable to traffic information system, travel information system, and location-based recommendation system which require retrieving nearest located object.

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Implementation of a Travel Route Recommendation System Utilizing Daily Scheduling Templates

  • Kim, Hyeon Gyu
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.10
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    • pp.137-146
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    • 2022
  • In relation to the travel itinerary recommendation service, which has recently become in high demand, our previous work introduces a method to quantify the popularity of places including tour spots, restaurants, and accommodations through social big data analysis, and to create a travel schedule based on the analysis results. On the other hand, the generated schedule was mainly composed of travel routes that connected tour spots with the shorted distance, and detailed schedule information including restaurants and accommodation information for each travel date was not provided. This paper presents an algorithm for constructing a detailed travel route using a scenario template in a travel schedule created based on social big data, and introduces a prototype system that implements it. The proposed system consists of modules such as place information collection, place-specific popularity score estimation, shortest travel rout generation, daily schedule organization, and UI visualization. Experiments conducted based on social reviews collected from 63,000 places in the Gyeongnam province proved effectiveness of the proposed system.

A Study on the Effect of Booth Recommendation System on Exhibition Visitors Unplanned Visit Behavior (전시장 참관객의 계획되지 않은 방문행동에 있어서 부스추천시스템의 영향에 대한 연구)

  • Chung, Nam-Ho;Kim, Jae-Kyung
    • Journal of Intelligence and Information Systems
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    • v.17 no.4
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    • pp.175-191
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    • 2011
  • With the MICE(Meeting, Incentive travel, Convention, Exhibition) industry coming into the spotlight, there has been a growing interest in the domestic exhibition industry. Accordingly, in Korea, various studies of the industry are being conducted to enhance exhibition performance as in the United States or Europe. Some studies are focusing particularly on analyzing visiting patterns of exhibition visitors using intelligent information technology in consideration of the variations in effects of watching exhibitions according to the exhibitory environment or technique, thereby understanding visitors and, furthermore, drawing the correlations between exhibiting businesses and improving exhibition performance. However, previous studies related to booth recommendation systems only discussed the accuracy of recommendation in the aspect of a system rather than determining changes in visitors' behavior or perception by recommendation. A booth recommendation system enables visitors to visit unplanned exhibition booths by recommending visitors suitable ones based on information about visitors' visits. Meanwhile, some visitors may be satisfied with their unplanned visits, while others may consider the recommending process to be cumbersome or obstructive to their free observation. In the latter case, the exhibition is likely to produce worse results compared to when visitors are allowed to freely observe the exhibition. Thus, in order to apply a booth recommendation system to exhibition halls, the factors affecting the performance of the system should be generally examined, and the effects of the system on visitors' unplanned visiting behavior should be carefully studied. As such, this study aims to determine the factors that affect the performance of a booth recommendation system by reviewing theories and literature and to examine the effects of visitors' perceived performance of the system on their satisfaction of unplanned behavior and intention to reuse the system. Toward this end, the unplanned behavior theory was adopted as the theoretical framework. Unplanned behavior can be defined as "behavior that is done by consumers without any prearranged plan". Thus far, consumers' unplanned behavior has been studied in various fields. The field of marketing, in particular, has focused on unplanned purchasing among various types of unplanned behavior, which has been often confused with impulsive purchasing. Nevertheless, the two are different from each other; while impulsive purchasing means strong, continuous urges to purchase things, unplanned purchasing is behavior with purchasing decisions that are made inside a store, not before going into one. In other words, all impulsive purchases are unplanned, but not all unplanned purchases are impulsive. Then why do consumers engage in unplanned behavior? Regarding this question, many scholars have made many suggestions, but there has been a consensus that it is because consumers have enough flexibility to change their plans in the middle instead of developing plans thoroughly. In other words, if unplanned behavior costs much, it will be difficult for consumers to change their prearranged plans. In the case of the exhibition hall examined in this study, visitors learn the programs of the hall and plan which booth to visit in advance. This is because it is practically impossible for visitors to visit all of the various booths that an exhibition operates due to their limited time. Therefore, if the booth recommendation system proposed in this study recommends visitors booths that they may like, they can change their plans and visit the recommended booths. Such visiting behavior can be regarded similarly to consumers' visit to a store or tourists' unplanned behavior in a tourist spot and can be understand in the same context as the recent increase in tourism consumers' unplanned behavior influenced by information devices. Thus, the following research model was established. This research model uses visitors' perceived performance of a booth recommendation system as the parameter, and the factors affecting the performance include trust in the system, exhibition visitors' knowledge levels, expected personalization of the system, and the system's threat to freedom. In addition, the causal relation between visitors' satisfaction of their perceived performance of the system and unplanned behavior and their intention to reuse the system was determined. While doing so, trust in the booth recommendation system consisted of 2nd order factors such as competence, benevolence, and integrity, while the other factors consisted of 1st order factors. In order to verify this model, a booth recommendation system was developed to be tested in 2011 DMC Culture Open, and 101 visitors were empirically studied and analyzed. The results are as follows. First, visitors' trust was the most important factor in the booth recommendation system, and the visitors who used the system perceived its performance as a success based on their trust. Second, visitors' knowledge levels also had significant effects on the performance of the system, which indicates that the performance of a recommendation system requires an advance understanding. In other words, visitors with higher levels of understanding of the exhibition hall learned better the usefulness of the booth recommendation system. Third, expected personalization did not have significant effects, which is a different result from previous studies' results. This is presumably because the booth recommendation system used in this study did not provide enough personalized services. Fourth, the recommendation information provided by the booth recommendation system was not considered to threaten or restrict one's freedom, which means it is valuable in terms of usefulness. Lastly, high performance of the booth recommendation system led to visitors' high satisfaction levels of unplanned behavior and intention to reuse the system. To sum up, in order to analyze the effects of a booth recommendation system on visitors' unplanned visits to a booth, empirical data were examined based on the unplanned behavior theory and, accordingly, useful suggestions for the establishment and design of future booth recommendation systems were made. In the future, further examination should be conducted through elaborate survey questions and survey objects.