• International Journal of Advanced Culture Technology
• /
• v.8 no.4
• /
• pp.263-270
• /
• 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.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2018.07a
• /
• pp.345-346
• /
• 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.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.37 no.8
• /
• pp.1139-1154
• /
• 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.

• Journal of Information Processing Systems
• /
• v.17 no.1
• /
• pp.14-27
• /
• 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.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.3
• /
• pp.407-413
• /
• 2020

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.

• Journal of the Institute of Convergence Signal Processing
• /
• v.20 no.3
• /
• pp.138-144
• /
• 2019

In a modern society, people are concerned seriously about their travel destinations depending on time, economic problem. In this paper, we propose an non-hierarchical clustering based hybrid recommendation using context knowledge. The proposed method is personalized way of recommended knowledge about preferred travel places according to the user's location, place, and weather. Based on 14 attributes from the data collected through the survey, users with similar characteristics are grouped using a non-hierarchical clustering based hybrid recommendation. This makes more accurate recommendation by weighting implicit and explicit data. The users can be recommended a preferred travel destination without spending unnecessary time. The performance evaluation uses accuracy, recall, F-measure. The evaluation result was shown 0.636 accuracy, 0.723 recall, and 0.676 F-measure.

• Journal of Korea Multimedia Society
• /
• v.17 no.8
• /
• pp.946-952
• /
• 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.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.61 no.2
• /
• pp.75-83
• /
• 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.

• Proceedings of the Korea Contents Association Conference
• /
• 2014.06a
• /
• pp.15-16
• /
• 2014

• Journal of Korea Spatial Information System Society
• /
• v.6 no.1 s.11
• /
• pp.59-71
• /
• 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.