• 제목/요약/키워드: Location Recommendation

검색결과 154건 처리시간 0.036초

소셜 사물인터넷에서 소셜 관계를 이용한 사물 추천 기법 (Things Recommendation Method using Social Relationship in Social Internet of Things)

  • 김성림;권준희
    • 디지털산업정보학회논문지
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    • 제10권3호
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    • pp.49-59
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    • 2014
  • The Internet of Things(IoT) is a new promising technology made from a variety of technology. The IoT links the objects or people, then enabling anytime, anywhere connectivity for anything and not only for anyone. Social networking services have changed the way people communicate. Recently, new research challenges in many areas of Internet of things and social networking services are fired. In this paper, we propose things recommendation method using social relationship in social Internet of Things. We study previous researches about social network service, IoT, and social IoT. We proposed SIoT_FW(Social IoT Friendship Weight) using static and a dynamic social friendship weight. Also, our method considers four social relationships (Ownership Object Relationship, Co-Location Object Relationship, Social Object Relationship, Parental Object Relationship). We presents a music device scenario using our proposed method.

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.

사용자 위치에 기반한 장소 추천 사이트의 구현 (Implementation of place recommendation site based on user's location)

  • 용승림;지창언
    • 한국컴퓨터정보학회:학술대회논문집
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    • 한국컴퓨터정보학회 2018년도 제58차 하계학술대회논문집 26권2호
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    • pp.345-346
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    • 2018
  • 본 논문에서는 사용자의 위치 정보를 입력받아 근처에 위치한 식당이나 어트랙션 장소를 추천하는 사이트를 구현하고 이를 제안한다. 웹 페이지를 통해 사용자의 위치정보를 입력 받고, SNS에서 추천하는 장소를 크롤링하여 데이터베이스를 구축하고 분석하여 식당과 어트랙션 장소를 추천해 준다. 추천 장소는 사용자에게 지도를 이용하여 그 위치를 보여주며 지도 위에 추천 장소의 간략 정보를 표시한다.

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패션점포 내 모바일 제품추천 서비스에 대한 소비자의 정보제공의도와 협력의도 (Consumers' Willingness to Provide Information and Cooperation Intention in the Use of Mobile Product Recommendation Services for Fashion Stores)

  • 이현화;문희강
    • 한국의류학회지
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    • 제37권8호
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    • pp.1139-1154
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    • 2013
  • This study examined the effects of consumers' usefulness and the hedonic perception of their willingness to provide information and cooperation intention in the use of location-context based mobile product recommendation services for fashion stores. We examined the influence of consumers' beliefs regarding marketer's information practices on their perceptions of provided services. In addition, the moderating effects of consumers' epistemic curiosity and information control level were investigated. A total of 400 smartphone users were included as participants for the present study. The results showed that consumers who perceived information services as more hedonic and useful are more likely to provide personal information and cooperate with marketers. The findings of the study suggest that fashion retailers who plan to introduce mobile product recommendation services should pay attention to the hedonic aspects of the services. In addition, the effects of usefulness and hedonic perception of the two dependent variables were different according to the level of epistemic curiosity and information control.

Development of a Targeted Recommendation Model for Earthquake Risk Prevention in the Whole Disaster Chain

  • Su, Xiaohui;Ming, Keyu;Zhang, Xiaodong;Liu, Junming;Lei, Da
    • Journal of Information Processing Systems
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    • 제17권1호
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    • pp.14-27
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    • 2021
  • Strong earthquakes have caused substantial losses in recent years, and earthquake risk prevention has aroused a significant amount of attention. Earthquake risk prevention products can help improve the self and mutual-rescue abilities of people, and can create convenient conditions for earthquake relief and reconstruction work. At present, it is difficult for earthquake risk prevention information systems to meet the information requirements of multiple scenarios, as they are highly specialized. Aiming at mitigating this shortcoming, this study investigates and analyzes four user roles (government users, public users, social force users, insurance market users), and summarizes their requirements for earthquake risk prevention products in the whole disaster chain, which comprises three scenarios (pre-quake preparedness, in-quake warning, and post-quake relief). A targeted recommendation rule base is then constructed based on the case analysis method. Considering the user's location, the earthquake magnitude, and the time that has passed since the earthquake occurred, a targeted recommendation model is built. Finally, an Android APP is implemented to realize the developed model. The APP can recommend multi-form earthquake risk prevention products to users according to their requirements under the three scenarios. Taking the 2019 Lushan earthquake as an example, the APP exhibits that the model can transfer real-time information to everyone to reduce the damage caused by an earthquake.

이벤트와 관련된 주변 관광지 자동 추천 알고리즘 개발 (Automatic Recommendation of Nearby Tourist Attractions related to Events)

  • 안진현;임동혁
    • 한국산학기술학회논문지
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    • 제21권3호
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    • pp.407-413
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    • 2020
  • 관광객이 관광 도중에 각종 문화제, 전시회, 공연 등의 이벤트에 참여하는 경우가 있다. 관광객이 이벤트에 참여 후 다음 관광지를 결정하게 되는데, 관광지 정보를 얻을 수 있는 수단은 지도 서비스, 블로그와 같은 소셜네트워크서비스 등이 존재한다. 지도 서비스를 활용하면 관광객이 현재 위치한 장소 주변의 관광지를 쉽게 검색할 수 있다. 이는 위치 기반 관광지 추천으로 활용될 수 있다. 블로그 등은 관광지의 내용을 담고 있기 때문에 관광객이 이벤트의 내용과 관련된 관광지를 찾을 수 있다. 이는 내용 기반 관광지 추천으로 활용될 수 있다. 하지만, 위치 기반 추천의 경우 이벤트의 내용과 관련이 없이 단순히 가까운 관광지가 추천이 될 수 있고, 내용 기반 추천의 경우 거리가 먼 관광지가 추천이 될 수 있는 단점이 있다. 위치와 내용을 모두 고려하는 관광지 추천 서비스는 거의 없다. 본 연구에서는 두 가지 방법의 장점만을 취하기 위해 한국관광공사 LOD(Linked Open Data), 위키피디아, 국어사전 등에 기반하여 위치와 내용을 모두 고려한 관광지 추천 알고리즘을 제시한다. 관광지의 설명글로부터 명사들을 추출한 뒤 다른 관광지의 명사들과 비교를 하여 동일한 명사가 많이 있을수록 내용이 관련이 있다고 판단한다. 정확히 동일한 명사가 없어도 위키피디아에 있는 키워드를 활용하여 관련된 명사가 존재할 경우에도 관련이 있다고 판단한다. 각 관광지의 위도와 경도를 기준으로 거리를 계산한 뒤 사용자가 선택한 가중치로 상기 내용 기반 관련도와 선형결합하여 추천순위를 계산한다.

상황 지식을 이용한 비계층적 군집 기반 하이브리드 추천 (Non-hierarchical Clustering based Hybrid Recommendation using Context Knowledge)

  • 백지원;김민정;박찬홍;정호일;정경용
    • 융합신호처리학회논문지
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    • 제20권3호
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    • pp.138-144
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    • 2019
  • 현대 사회에서 사람들은 시간적인 여유, 경제적인 문제 등에 따라 여행지에 대해 심각한 고민을 한다. 따라서 본 논문에서는 상황 지식을 이용한 비계층적 군집 기반 하이브리드 추천을 제안한다. 제안하는 방법은 사용자의 위치, 장소, 날씨 등의 상황에 따라 선호하는 여행지에 대한 지식을 추천받을 수 있는 개인화된 방법이다. 설문조사를 통해 수집된 데이터로부터 14개의 속성을 기반으로 유사한 특성을 가진 사용자들을 비계층적 군집 기반 하이브리드 추천을 이용하여 군집한다. 이는 암묵적 데이터와 명시적 데이터에 가중치를 부여하여 보다 정확한 추천을 한다. 이를 통해 사용자는 불필요한 시간을 소모하지 않고 선호하는 여행지를 추천받을 수 있다. 성능평가는 정확도, 재현율, F-measure를 이용한다. 평가 결과 정확도는 0.636, 재현율은 0.723, F-measure는 0.676으로 평가되었다.

Mobility Prediction Algorithms Using User Traces in Wireless Networks

  • Luong, Chuyen;Do, Son;Park, Hyukro;Choi, Deokjai
    • 한국멀티미디어학회논문지
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    • 제17권8호
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    • pp.946-952
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    • 2014
  • Mobility prediction is one of hot topics using location history information. It is useful for not only user-level applications such as people finder and recommendation sharing service but also for system-level applications such as hand-off management, resource allocation, and quality of service of wireless services. Most of current prediction techniques often use a set of significant locations without taking into account possible location information changes for prediction. Markov-based, LZ-based and Prediction by Pattern Matching techniques consider interesting locations to enhance the prediction accuracy, but they do not consider interesting location changes. In our paper, we propose an algorithm which integrates the changing or emerging new location information. This approach is based on Active LeZi algorithm, but both of new location and all possible location contexts will be updated in the tree with the fixed depth. Furthermore, the tree will also be updated even when there is no new location detected but the expected route is changed. We find that our algorithm is adaptive to predict next location. We evaluate our proposed system on a part of Dartmouth dataset consisting of 1026 users. An accuracy rate of more than 84% is achieved.

입지계수를 이용한 지역 농특산물 지리적표시제의 정량적 평가기준 연구 (Quantitative Evaluation on Geographical Indication of Agricultural Specialty Products using Location Quotient (LQ) Index)

  • 김솔희;서교;김유안;김찬우;정찬훈
    • 한국농공학회논문집
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    • 제61권2호
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    • pp.75-83
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    • 2019
  • Using geographical indication, a type of source identification, can effectively promote local specialty agricultural products of superior quality, by identifying the specific geographic location or origin of the produce. Agricultural products can be registered using the geographical indication by describing the product's relation to its geographical origin including the reputation and quality. However, this indication has no objective standards to qualify goods as agricultural specialty products. The purpose of this study is to suggest basic criteria to define the characteristics and criteria of agricultural specialties based on a quantitative evaluation method. To propose this basic standard, we used the proportion of arable land to denote the major production areas and the location quotient (LQ) index to grasp the extent of the specialty of a product. The results show that the average LQ values of registered agricultural products, particularly apples, pears, and garlic, are 3.26, 8.01, and 2.82, respectively. This indicates that they are more specialized than produce from other areas that have not registered for a geographical indication. Low LQ values were found in some areas with registered rice geographical indications, which are also more focused on their historical reputation as the main rice producing areas. Considering the agricultural specialty of products, the recommendation is that the producing proportion should be over 1% of the national scale and over 10% of the province scale, and the LQ value should be over 2.0. This recommendation is not a requirement, but the criteria can prove to be useful in identifying a higher range of specialized agricultural products.