• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.185-205
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• 2023

As the tourism industry recovers post the COVID-19 pandemic, an increasing number of tourists are utilizing various platforms to leave reviews. However, amidst the vast amount of data, finding useful information remains challenging, often leading to time and cost inefficiencies in selecting travel destinations. Despite ongoing research, there are limitations due to the absence of ratings or the presence of different rating formats across platforms. Moreover, inconsistencies between ratings and the content of reviews pose challenges in developing recommendation models. To address these issues, this study utilized 7,104 reviews of tourist spots in Jeju Island to develop a specialized satisfaction index for Jeju tourist attractions and employed this index to construct a 'Rating Prediction Model.' To validate the model's performance, we predicted the ratings of 700 experimental data points using both the developed model and an LSTM approach. The proposed model demonstrated superior performance with a weighted accuracy of 73.87%, which is approximately 4.67% higher than that of the LSTM. The results of this study are expected to resolve the discrepancies between ratings and review contents, standardize ratings in reviews without ratings or in various formats, and provide reliable rating indicators applicable across all areas of travel in different domains.

• Smart Media Journal
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• v.12 no.8
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• pp.26-36
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• 2023

The purpose of this study is to propose ways to revitalize the local economy by analyzing the index changes and tourism big data before and after the opining of the KTX on the Gangneung Line in Gangneung City, where the population continues to decline. For This, the main current status of Gangneung-si and internal operation record data(DTG) of Gangneung-si were analyzed. After that, changes in the movement behavior of public transportation users before and after the opening of the KTX Gangneung Line were compared. As a result, it was possible to observe changes in tourist transportation preferences, demographic shifts, alterations in small-scale business sectors and in the travel patterns of tourists within the city of Gangneung. In particular, changes in the small business sector have shown an increase in general restaurants, leisure food establishments(cafes, etc.), and accommodation facilities following the opening of the KTX Gangneung Line. All three sectors have experienced growth concentrated in the vicinity of Gangneung Station, indicating the influence of Gangneung Station, which opened in the central part of Gangneung city, following the inauguration of the KTX Gangneung Line.

• Management & Information Systems Review
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• v.36 no.4
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• pp.129-148
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• 2017

Conventional exhibition management information systems recommend tourist attractions that are close to the place in which an exhibition is held. Some recommended attractions by the location-based recommendation could be meaningless when nothing is related to the exhibition's topic. Our goal is to recommend attractions that are related to the content presented in the exhibition, which can be coined as content-based recommendation. Even though human exhibition curators can do this, the quality is limited to their manual task and knowledge. We propose an automatic way of discovering attractions relevant to an exhibition of interests. Language resources are incorporated to discover attractions that are more meaningful. Because a typical single machine is unable to deal with such large-scale language resources efficiently, we implemented the algorithm on top of Apache Spark, which is a well-known distributed computing framework. As a user interface prototype, a web-based system is implemented that provides users with a list of relevant attractions when users are browsing exhibition information, available at http://bike.snu.ac.kr/WARP. We carried out a case study based on Korean Tourism Organization Linked Open Data with Korean Wikipedia as a language resource. Experimental results are demonstrated to show the efficiency and effectiveness of the proposed system. The effectiveness was evaluated against well-known exhibitions. It is expected that the proposed approach will contribute to the development of both exhibition and tourist industries by motivating exhibition visitors to become active tourists.

• Knowledge Management Research
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• v.23 no.1
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• pp.187-201
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• 2022

Online reviews written by tourists provide important information for the management and operation of the tourism industry. The star rating of online reviews is a simple quantitative evaluation of a product or service, but it is difficult to reflect the sincere attitude of tourists. There is also an issue; the star rating and review content are not matched. In this study, a star rating prediction model based on online review content was proposed to solve the discrepancy problem. We compared the differences in star ratings and sentiment by continent through sentiment analysis on tourist attractions and hotels written by foreign tourists who visited Korea. Variables were selected through TF-IDF vectorization and sentiment analysis results. Logit, artificial neural network, and SVM(Support Vector Machine) were used for the classification model, and artificial neural network and SVR(Support Vector regression) were applied for the rating prediction model. The online review rating prediction model proposed in this study could solve inconsistency problems and also could be applied even if when there is no star rating.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.167-181
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• 2023

This study utilized TEXTOM, a social network analysis program to analyze changes in current tourism behavior after travel restrictions were eased after the outbreak of COVID-19. Data on the keywords 'domestic travel' and 'overseas travel' were collected from blogs, cafes, and news provided by Naver, Google, and Daum. The collection period was set from April to December 2022 when social distancing was lifted, and 2019 and 2020 were each set as one year and compared and analyzed with 2022. A total of 80 key words were extracted through text mining and centrality analysis was performed using NetDraw. Finally, through the CONCOR, the correlated keywords were clustered into 4. As a result of the study, tourism behavior in 2022 shows tourism recovery before the outbreak of COVID-19, segmentation of travel based on each person's preferred theme, prioritization of each country's corona mitigation policy, and then selecting a tourist destination. It is expected to provide basic data for the development of tourism marketing strategies and tourism products for the newly emerging tourism ecosystem after COVID-19.

• Journal of Digital Convergence
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• v.13 no.10
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• pp.185-194
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• 2015

We are living in big data. Specially, female consumers are the hottest issue. Female consumers have a great effected on consumer culture as comparing male consumers. Therefore, this study analysis characteristics of female consumers through case study and literature review. The summarized results of research are as follows. First, percentage of economically active population of unmarried female of 20s is high, so they actively spend lots of money on buying goods and so on. Second, they are ahead of the curve and follow entertainers. Third, domestic case studies(SD online buz marketing, C.S.I. Shinsegaemall project, Service center only for female consumers of Shinhan Card, Travel Service of Lotte Tour) and international case studies(Big data service of Target, ZARA, and Walmart) show that if we utilize big data, we can raise re-purchasing desire and analysis needs of female consumers and create new female consumers.

• Journal of the Korean Society for information Management
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• v.35 no.1
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• pp.13-32
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• 2018

The purpose of this study is to analyze the association among the subject areas of big data research papers. The subject group of the units of analysis was extracted by applying co-citation networks, and the rules of association were analyzed using Apriori algorithm of R program, and visualized using the arulesViz package of R program. As a result of the study, 22 subject areas were extracted and these subjects were divided into three clusters. As a result of analyzing the association type of the subject, it was classified into 'professional type', 'general type', 'expanded type' depending on the complexity of association. The professional type included library and information science and journalism. The general type included politics & diplomacy, trade, and tourism. The expanded types included other humanities, general social sciences, and general tourism. This association networks show a tendency to cite other subject areas that are relevant when citing a subject field, and the library should consider services that use the association for academic information services.

• Journal of Service Research and Studies
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• v.12 no.1
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• pp.25-35
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• 2022

Covid-19, of which the first patient in Korea occurred in January 2020, has affected various fields. Of these, the tourism sector might havebeen hit the hardest. In particular, since tourism-based industrial structure forms the basis of the region, Gangwon-province, and the tourism industry is the main source of income for small businesses and small enterprises, the damage is great. To check the situation and extent of such damage, targeting the Chuncheon region, where public access is the most convenient among the Gangwon regions, one-day tours are possible using public transportation from Seoul and the metropolitan area, with a general image that low expense tourism is recognized as possible, this study conducted empirical analysis through data analysis. For this, the general status of the region was checked based on the visitor data of Chuncheon city provided by the tourist information system, and to check the levels ofinterest in 2019, before Covid-19, and in 2020, after Covid-19, by comparing keywords collected from the web service sometrend of Vibe Company Inc., a company specializing in keyword collection, with SK Telecom's T-map search site data, which in parallel provides in-vehicle navigation service and communication service, this study analyzed the general regional image of Chuncheon-city. In addition, by comparing data from two years by developing a tourism popularity index applying keywords and T-map search site data, this study examined how much the Covid-19 situation affected the level of interest of visitors to the Chuncheon area leading to actual visits using a data analysis approach. According to the results of big data analysis applying the tourism popularity index after designing the data mart, this study confirmed that the effect of the Covid-19 situation on tourism popularity in Chuncheon-city, Gangwon-provincewas not significant, and confirmed the image of tourist destinations based on the regional characteristics of the region. It is hoped that the results of this research and analysis can be used as useful reference data for tourism economic policy making.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.637-639
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• 2019

최근 관광산업은 AI, 빅데이터, IoT, 증강현실 등 4 차 산업혁명 관련 기술이 활용을 활용하여 관광산업 활성화를 도모하고 있다. 모바일 애플리케이션을 통한 개인 맞춤형 서비스가 다수 개발되고 있으나, 낙후된 지역사회 관광지에는 아직까지 테마로드 같은 콘텐츠 개발이 미비한 상황이다. 이에 본 연구에서는 QR 코드, 블루투스, 비콘 등의 기술을 기반으로 사용자가 쉽게 이용할 수 있는 위치 기반 서비스 알고리즘을 개발하고자 하며 이를 통해 침체된 구도시의 관광객 유치와 관람객들이 재미있게 활용할 수 있는 테마로드 콘텐츠를 제공하고자 한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.10-10
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• 2020

하천은 최근 주민에게 휴식과 레저의 기회를 제공하고 지역활기 창출의 자원으로 가치가 부상함에 따라 하천공간의 관리와 운영이 한층 더 중요해 졌다. 즉 하천공간의 개발과 보전은 지역의 문화관광과 복지 등의 지역 정책과 함께 하천이용의 수요를 고려하여 신중하게 운영해야 한다. 이에 본 연구에서는 하천공간의 체계적인 관리를 위해 통신 빅데이터를 활용하여 이용객 수를 추정하고 검증 한 뒤, 이용도 지표를 산정하였으며, 하천공간의 상세 유형화 방안을 마련하고 유형별 특성분석 등을 실시하고자 하였다. 현장표본조사를 통한 검증결과 통신 빅데이터는 하천공간에서의 이용객 수 추정에 활용 가능성을 보였으며, 이용도 지표 산정결과를 통해 친구지구를 이용객들이 어떻게 활용하는지 판단할 수 있었다. 또한 상세 유형화 방안을 마련하고 적용한 결과 이용객들이 하천공간을 근린의 성격과 거점의 성격으로 이용하고 있는지 판단할 수 있었다. 본 연구의 결과를 종합할 때, 친수지구 조성 및 관리를 위한 자료 활용방안을 제시할 수 있었으며, 국가하천 점용허가 시 통신 빅데이터 활용방안을 마련할 수 있었다. 통신 빅데이터는 친수지구 이용도 조사에 크게 유용한 방법을 제공하며, 하천계획, 유지·보수 등 관련 실무활용 및 정책수립에 큰 도움이 될 것으로 판단된다.