• 제목/요약/키워드: Smart Tourism Chatbot

검색결과 11건 처리시간 0.019초

Personal Smart Travel Planner Service

  • Ki-Beom Kang;Myeong Gyun Kang;Seong-Hyuk Jo;Jeong-Woo Jwa
    • International Journal of Advanced Culture Technology
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    • 제11권4호
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    • pp.385-392
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    • 2023
  • The smart tourism service provides tourists with personal travel planner services and context-awareness-based tour guide services. In this paper, we propose the personal travel planner service that creates my travel itinerary using the smart tourism app and the travel planner system. The smart tourism app provides recommended travel products and POI tourist information used to create my travel itinerary. The smart tourism app also provides the smart tourism chatbot service that allows users to select POI tourist information easily and conveniently. The travel planner system consists of the smart tourism information system and the smart tourism chatbot system. The smart tourism information system provides users with travel planner services, recommended travel products, and POI tourism information through the smart tourism app. The smart tourism chatbot system consists of named entity recognition (NER), dialogue state tracking (DST), and Neo4J servers, and provides chatbot services as a smart tourism app. Users can create their own travel itinerary, modify the travel itinerary while traveling, and then register it as a recommended travel product to users, including acquaintances.

Development of Tourism Information Named Entity Recognition Datasets for the Fine-tune KoBERT-CRF Model

  • Jwa, Myeong-Cheol;Jwa, Jeong-Woo
    • International Journal of Internet, Broadcasting and Communication
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    • 제14권2호
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    • pp.55-62
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    • 2022
  • A smart tourism chatbot is needed as a user interface to efficiently provide smart tourism services such as recommended travel products, tourist information, my travel itinerary, and tour guide service to tourists. We have been developed a smart tourism app and a smart tourism information system that provide smart tourism services to tourists. We also developed a smart tourism chatbot service consisting of khaiii morpheme analyzer, rule-based intention classification, and tourism information knowledge base using Neo4j graph database. In this paper, we develop the Korean and English smart tourism Name Entity (NE) datasets required for the development of the NER model using the pre-trained language models (PLMs) for the smart tourism chatbot system. We create the tourism information NER datasets by collecting source data through smart tourism app, visitJeju web of Jeju Tourism Organization (JTO), and web search, and preprocessing it using Korean and English tourism information Name Entity dictionaries. We perform training on the KoBERT-CRF NER model using the developed Korean and English tourism information NER datasets. The weight-averaged precision, recall, and f1 scores are 0.94, 0.92 and 0.94 on Korean and English tourism information NER datasets.

Development of a Tourism Information QA Service for the Task-oriented Chatbot Service

  • Hoon-chul Kang;Myeong-Gyun Kang;Jeong-Woo Jwa
    • International Journal of Advanced Culture Technology
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    • 제12권3호
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    • pp.73-79
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    • 2024
  • The smart tourism chatbot service provide smart tourism services to users easily and conveniently along with the smart tourism app. In this paper, the tourism information QA (Question Answering) service is proposed based on the task-oriented smart tourism chatbot system [13]. The tourism information QA service is an MRC (Machine reading comprehension)-based QA system that finds answers in context and provides them to users. The tourism information QA system consists of NER (Named Entity Recognition), DST (Dialogue State Tracking), Neo4J graph DB, and QA servers. We propose tourism information QA service uses the tourism information NER model and DST model to identify the intent of the user's question and retrieves appropriate context for the answer from the Neo4J tourism knowledgebase. The QA model finds answers from the context and provides them to users through the smart tourism app. We develop the tourism information QA model by transfer learning the bigBird model, which can process the context of 4,096 tokens, using the tourism information QA dataset.

Development of the Rule-based Smart Tourism Chatbot using Neo4J graph database

  • Kim, Dong-Hyun;Im, Hyeon-Su;Hyeon, Jong-Heon;Jwa, Jeong-Woo
    • International Journal of Internet, Broadcasting and Communication
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    • 제13권2호
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    • pp.179-186
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    • 2021
  • We have been developed the smart tourism app and the Instagram and YouTube contents to provide personalized tourism information and travel product information to individual tourists. In this paper, we develop a rule-based smart tourism chatbot with the khaiii (Kakao Hangul Analyzer III) morphological analyzer and Neo4J graph database. In the proposed chatbot system, we use a morpheme analyzer, a proper noun dictionary including tourist destination names, and a general noun dictionary including containing frequently used words in tourist information search to understand the intention of the user's question. The tourism knowledge base built using the Neo4J graph database provides adequate answers to tourists' questions. In this paper, the nodes of Neo4J are Area based on tourist destination address, Contents with property of tourist information, and Service including service attribute data frequently used for search. A Neo4J query is created based on the result of analyzing the intention of a tourist's question with the property of nodes and relationships in Neo4J database. An answer to the question is made by searching in the tourism knowledge base. In this paper, we create the tourism knowledge base using more than 1300 Jeju tourism information used in the smart tourism app. We plan to develop a multilingual smart tour chatbot using the named entity recognition (NER), intention classification using conditional random field(CRF), and transfer learning using the pretrained language models.

Suggested social media big data consulting chatbot service for restaurant start-ups

  • Jong-Hyun Park;Jun-Ho Park;Ki-Hwan Ryu
    • International journal of advanced smart convergence
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    • 제12권3호
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    • pp.68-74
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    • 2023
  • The food industry has been hit hard since the first outbreak of COVID-19 in 2019. However, as of April 2022, social distancing has been resolved and the restaurant industry has gradually recovered, interest in restaurant start-ups is increasing. Therefore, in this paper, 'restaurant start-up' was cited as a key keyword through social media big data analysis using TexTom, and word frequency and cone analysis were conducted for big data analysis. The keyword collection period was selected from May 1, 2022, when social distancing due to COVID-19 was lifted, to May 23, 2023, and based on this, a plan to develop chatbot services for restaurant start-ups was proposed. This paper was prepared in consideration of what to consider when starting a restaurant and a chatbot service that allows prospective restaurant founders to receive information more conveniently. Based on these analysis results, we expected to contribute to the process of developing chatbots for prospective restaurant founders in the future

Proposed a consulting chatbot service for restaurant start-ups using social media big data

  • Jong-Hyun Park;Yang-Ja Bae;Jun-Ho Park;Ki-Hwan Ryu
    • International Journal of Internet, Broadcasting and Communication
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    • 제15권3호
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    • pp.1-7
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    • 2023
  • Since the first outbreak of COVID-19 in 2019, it has caused a huge blow to the restaurant industry. However, as social distancing was lifted as of April 2022, the restaurant industry gradually recovered, and as a result, interest in restaurant start-ups increased. Therefore, in this paper, big data analysis was conducted by selecting "restaurant start-up" as a key keyword through social media big data analysis using Textom and then conducting word frequency and CONCOR analysis. The collection period of keywords was selected from May 1, 2022 to May 23, 2023, after the lifting of social distancing due to COVID-19, and based on the analysis, the development of a restaurant start-up consulting chatbot service is proposed.

Recommendation of tourist attractions based on Preferences using big data

  • KIM HYUN SEOK;Gi-hwan Ryu;kim im yeo-reum
    • International Journal of Advanced Culture Technology
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    • 제11권3호
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    • pp.327-331
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    • 2023
  • This paper proposes a tourist destination recommendation application that combines a chatbot and a recommendation system. The data to be entered into the chatbot was through big data on social media. Through TEXTOM, a total of 22,701 data were collected over a one-year period from January 2022 to January 2023. Non-terms that interfere with analysis were removed through the data purification process. Using refined data, network visualization and CONCOR analysis were used to identify the information users want to obtain about travel to Jeju Island, and categories for each cluster were organized. The content was intuitively organized so that even those who approached it for the first time could easily use it, reducing the difficulty of operating the application. In this paper, users can select their own preferences and receive information. In addition, a tool called a chatbot allows users to focus more on the process of acquiring information by gaining a sense of reality while operating the application. This suggests an application that can reach the purpose of the curator by affecting the user's desire to visit tourist attractions.

The study on Analysis of factors of restaurant start-ups using big data

  • JINHO LEE;Sung woo Park;Gi-Hwan Ryu
    • International journal of advanced smart convergence
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    • 제12권3호
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    • pp.163-167
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    • 2023
  • The restaurant industry is an industry with low entry barriers, and furthermore, it is an indispensable industry in life. However, for the restaurant industry, it is necessary to start a business considering many factors. In particular, the comparative group for each restaurant industry is different, and the commercial area analysis should be analyzed differently. Moreover, counseling for restaurant start-ups is still sticking to how to start a restaurant by meeting with each franchise supervisor or counselor. Therefore, a restaurant start-up chatbot is needed for prospective restaurant founders, and a food tech chatbot is needed to collect basic data. Therefore, in this study, factors for restaurant start-ups were divided into youth, preliminary start-ups, menus, taste, and food. In the case of restaurant start-ups with low entry barriers, it was confirmed as the most preferred start-up by young people. However, indiscriminate restaurant start-ups not only increase the closing rate but also have a significant impact on household debt, so accurate consulting should be used to lower the closing rate and increase the success rate. Furthermore, theories and measures for food technologies such as chatbots should be further developed to obtain accurate information on franchise start-ups.

ChatGPT, 대화형 인공지능 관광 검색 서비스의 행동의도에 대한 연구: 인지적 신뢰와 정서적 신뢰의 역할을 중심으로 (A Study of the Behavioral Intention on Conversational ChatGPT for Tourism Information Search Service: Focusing on the Role of Cognitive and Affective Trust)

  • 김민성;구철모
    • 경영정보학연구
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    • 제26권1호
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    • pp.119-149
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    • 2024
  • 이 연구는 여행 정보 검색 서비스로서 ChatGPT와 같은 새로운 AI 챗봇의 신뢰 형성과 행동 의도에 미치는 선행 요소와 메커니즘을 탐구한다. 연구는 익숙함, 참신함, 개인의 혁신성, 정보의 질, 그리고 지각된 의인화 등 다양한 변수들 간의 관계를 분석하여, 이러한 요인들이 사용자의 인지적, 정서적 신뢰와 궁극적으로 정보수용의도, 지속사용의도에 미치는 영향을 규명한다. 결과적으로, 익숙함과 정보의 질은 인지적, 정서적 신뢰 모두에 영향을 미치는 반면 참신함은 인지적 신뢰에만 긍정적으로 기여했다. 더불어, 새로운 AI 챗봇 사용자의 개인적 혁신성은 익숙함과 인지적 신뢰 간의 관계를 약화시키는 한편, 챗봇의 지각된 의인화 수준은 참신함 및 익숙함과 인지적 신뢰 간의 관계를 증폭시키는 것으로 나타났다. 이러한 결과는 AI 챗봇의 디자인과 도입 시 의인화, 정보의 질 익숙함, 개인의 혁신성 등의 측면을 고려하는 중요성을 강조하며, 이를 통해 새로운 AI 챗봇의 여행 정보 검색 서비스로서 신뢰 및 행동의도 형성에 기여할 것으로 기대된다.

A Study on the Restaurant Recommendation Service App Based on AI Chatbot Using Personalization Information

  • Kim, Heeyoung;Jung, Sunmi;Ryu, Gihwan
    • International Journal of Advanced Culture Technology
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    • 제8권4호
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    • pp.263-270
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    • 2020
  • The growth of the mobile app markets has made it popular among people who recommend relevant information about restaurants. The recommendation service app based on AI Chatbot is that it can efficiently manage time and finances by making it easy for restaurant consumers to easily access the information they want anytime, anywhere. Eating out consumers use smartphone applications for finding restaurants, making reservations, and getting reviews and how to use them. In addition, social attention has recently been focused on the research of AI chatbot. The Chatbot is combined with the mobile messenger platform and enabling various services due to the text-type interactive service. It also helps users to find the services and data that they need information tersely. Applying this to restaurant recommendation services will increase the reliability of the information in providing personal information. In this paper, an artificial intelligence chatbot-based smartphone restaurant recommendation app using personalization information is proposed. The recommendation service app utilizes personalization information such as gender, age, interests, occupation, search records, visit records, wish lists, reviews, and real-time location information. Users can get recommendations for restaurants that fir their purpose through chatting using AI chatbot. Furthermore, it is possible to check real-time information about restaurants, make reservations, and write reviews. The proposed app uses a collaborative filtering recommendation system, and users receive information on dining out using artificial intelligence chatbots. Through chatbots, users can receive customized services using personal information while minimizing time and space limitations.