• Title, Summary, Keyword: Place Recommendation

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Development of User-dependent Mid-point Navigation System (사용자 중심의 중간지점 탐색 시스템의 설계 및 구현)

  • Ahn, Jonghee;Kang, Inhyeok;Seo, Seyeong;Kim, Taewoo;Heo, Yusung;Ahn, Yonghak
    • Convergence Security Journal
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    • v.19 no.2
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    • pp.73-81
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    • 2019
  • In this paper, we propose a user-dependent mid-point navigation system using a time weighted mid-point navigation algorithm and a user preference based mid-point neighborhood recommendation system. The proposed system consists of a mid-point navigation module for calculating an mid-point by applying a time weight of each user based on a departure point between users, and a search module for providing a search for a route to the calculated mid-point. In addition, based on the mid-point search result, it is possible to increase the utilization rate of users by including a place recommending function based on user's preference. Experimental results show that the proposed system can increase the efficiency of using by the user-dependent mid-point navigation and place recommendation function.

Design and Implementation of Agent-Recruitment Service System based on Collaborative Deep Learning for the Intelligent Head Hunting Service (지능형 헤드헌팅 서비스를 위한 협업 딥 러닝 기반의 중개 채용 서비스 시스템 설계 및 구현)

  • Lee, Hyun-ho;Lee, Won-jin
    • Journal of Korea Multimedia Society
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    • v.23 no.2
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    • pp.343-350
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    • 2020
  • In the era of the Fourth Industrial Revolution in the digital revolution is taking place, various attempts have been made to provide various contents in a digital environment. In this paper, agent-recruitment service system based on collaborative deep learning is proposed for the intelligent head hunting service. The service system is improved from previous research [7] using collaborative deep learning for more reliable recommendation results. The Collaborative deep learning is a hybrid recommendation algorithm using "Recurrent Neural Network(RNN)" specialized for exponential calculation, "collaborative filtering" which is traditional recommendation filtering methods, and "KNN-Clustering" for similar user analysis. The proposed service system can expect more reliable recommendation results than previous research and showed high satisfaction in user survey for verification.

Canonical Correlations between Benefit Sought and Selection Attributes of Green Tea Consumers (녹차소비자의 추구편익과 선택속성의 관계)

  • Kim, Kyung-Hee;Park, Duk-Byeong
    • The Korean Journal of Community Living Science
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    • v.22 no.3
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    • pp.327-339
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    • 2011
  • This study aims to investigate relationships between benefit sought and selection attributes of green tea consumers. For data collection, a total of 595 copies of questionnaires were collected by convenience sampling in the Seoul and Gyeonggi-do area. The data were analyzed by using SPSS 15.0. The factor analysis identified four dimensions of the benefit sought : health benefit, sensory, sociality, and self-esteem. Six dimensions of selection attributes were identified as manufacturing, design, sensory appeal, recommendation, utility and brand. The results of the canonical correlation analysis indicated that health benefit, sensory, sociality of benefit sought and manufacturing, design, sensory appeal, recommendation, utility, brand of selection attributes were highly correlated, and the self-esteem of benefit sought and recommendation of selection attribute were highly correlated. This means it is important to place an emphasis on safety production, package design, sensory characteristics, product description, utility and brand for consumers who seek health benefit, flavor and sociality. It is also important to place an emphasis on product description for consumers who pursue self-esteem benefits. Green tea marketers should consider benefit sought aspects as the most important factors affecting selection attributes on green tea purchasing.

A Study on Recommendation Systems based on User multi-attribute attitude models and Collaborative filtering Algorithm (다속성 태도 모델과 협업적 필터링 기반 장소 추천 연구)

  • Ahn, Byung-Ik;Jung, Ku-Imm;Choi, Hae-Lim
    • Smart Media Journal
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    • v.5 no.2
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    • pp.84-89
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    • 2016
  • For a place-recommendation model based on user's behavior and multi-attribute attitude in this thesis. We focus groups that show similar patterns of visiting restaurants and then compare one and the other. We make use of The Fishbein Equation, Pearson's Correlation Coefficient to calculate multi-attribute attitude scores. Furthermore, We also make use of Preference Prediction Algorithm and Distance based method named "Euclidean Distance" to provide accurate results. We can demonstrate how excellent this system is through several experiments carried out with actual data.

Hybrid Recommendation Based Brokerage Agent Service System under the Compound Logistics (공동물류 환경의 혼합추천시스템 기반 차주-화주 중개서비스 구현)

  • Jang, Sangyoung;Choi, Myoungjin;Yang, Jaekyung
    • Journal of the Society of Korea Industrial and Systems Engineering
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    • v.39 no.4
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    • pp.60-66
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    • 2016
  • Compound logistics is a service aimed to enhance logistics efficiency by supporting that shippers and consigners jointly use logistics facilities. Many of these services have taken place both domestically and internationally, but the joint logistics services for e-commerce have not been spread yet, since the number of the parcels that the consigners transact business is usually small. As one of meaningful ways to improve utilization of compound logistics, we propose a brokerage service for shipper and consigners based on the hybrid recommendation system using very well-known classification and clustering methods. The existing recommendation system has drawn a relatively low satisfaction as it brought about one-to-one matches between consignors and logistics vendors in that such matching constrains choice range of the users to one-to-one matching each other. However, the implemented hybrid recommendation system based brokerage agent service system can provide multiple choice options to mutual users with descending ranks, which is a result of the recommendation considering transaction preferences of the users. In addition, we applied feature selection methods in order to avoid inducing a meaningless large size recommendation model and reduce a simple model. Finally, we implemented the hybrid recommendation system based brokerage agent service system that shippers and consigners can join, which is the system having capability previously described functions such as feature selection and recommendation. As a result, it turns out that the proposed hybrid recommendation based brokerage service system showed the enhanced efficiency with respect to logistics management, compared to the existing one by reporting two round simulation results.

A Recommendation System Based on Customer Preference Analysis and Filter Management (고객 성향 분석과 필터 관리 기반 추천 시스템)

  • 이성구
    • Journal of Korea Multimedia Society
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    • v.7 no.4
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    • pp.592-600
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    • 2004
  • A recommendation system, which is an application area of e-CRM in e-commerce environment, provides individualized goods recommendation service that meets the demand of individual users. In general, existing recommendation systems require extensive historic user information in application domains. However, the method of recommendation based on static historic user information needs to respond flexibly to users'demand that changes rapidly and sensitively over time and in domains including a variety of users. In addition, it is difficult to recommend for new users who are not fall into any of existing domains. To overcome such limitations and provide flexible recommendation service, this study designed and implemented CPAR (Customer Preference Analysis Recommender) system that supports customer preference analysis and filter management. The filtering management capacity of the present system eases the necessity of extensive information about new users. In addition, CPAR system was implemented in XML-based wireless Internet environment for recommendation service independent from platforms and not limited by time and place.

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The Effect of Selection Attributes for Makgeolli on the Customer Satisfaction, Repurchase Intention and Recommendation Intention (막걸리의 선택 속성이 만족도와 추천 의도, 재구매 의도에 미치는 영향)

  • Kim, Young-Gab;Kim, Sun-Hee
    • Journal of the East Asian Society of Dietary Life
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    • v.20 no.3
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    • pp.389-395
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    • 2010
  • This research was focused on observing the effect of Makgeolli's selection attributes on customer satisfaction, recommendation intention, and repurchase intention. The purpose of this study was to examine to present a marketing-related suggestion by finding the components that needs to be discussed in order to satisfy the customer and lead to positive word of mouth and repurchasing in the perspective of a corporation. The evidence to achieve the research purpose can be summarized as below. To begin with, the causes of Makgeolli's selection attributes were classified into 9 types, which are design and ad image, expertise and tradition, drinking experience and in harmony with food, taste and freshness, materials and origin, brand image, flavor and color, alcoholic and nutrition, and finally price and recommendation. And it showed up that the average importance of the taste and freshness is the highest. Moreover, the study on the Makgeolli's state of being potable showed up that the drinking number was no more than once a month, and one drink was almost all less than a bottle. The drinking place was usually tavern, and word of mouth was the most often used information medium that contacted Makgeolli. The potential of the Makgeolli's globalization is 80.6% which added positive and very positive, that enables us to infer that the Makgeolli's global dependency is very high. Third, from the 9 types of classification mentioned before, taste and freshness, and price and recommendation were proved to be influential in satisfaction, and recommendation is affecting the repurchase intention and the recommendation intention.

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

  • Baek, Ji-Won;Kim, Min-Jeong;Park, Roy C.;Jung, Hoill;Chung, Kyungyong
    • Journal of the Institute of Convergence Signal Processing
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    • v.20 no.3
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    • pp.138-144
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    • 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.

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Recommending Personalized POI Considering Time and User Activity in Location Based Social Networks (위치기반 소셜 네트워크에서 시간과 사용자 활동을 고려한 개인화된 POI 추천)

  • Lee, Kyunam;Lim, Jongtae;Bok, Kyoungsoo;Yoo, Jaesoo
    • The Journal of the Korea Contents Association
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    • v.18 no.1
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    • pp.64-75
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    • 2018
  • With the development of location-aware technologies and the activation of smart phones, location based social networks(LBSN) have been activated to allow people to easily share their location. In particular, studies on recommending the location of user interests by using the user check-in function in LBSN have been actively conducted. In this paper, we propose a location recommendation scheme considering time and user activities in LBSN. The proposed scheme considers user preference changes over time, local experts, and user interest in rare places. In other words, it uses the check-in history over time and distinguishes the user activity area to identify local experts. It also considers a rare place to give a weight to the user preferred place. It is shown through various performance evaluations that the proposed scheme outperforms the existing schemes.

The Analysis of Satisfaction in Wando Changpogo Festival (완도 장보고축제의 만족도 분석)

  • Ahn, Zong-Hyun;Lee, Jeong-Rock
    • Journal of the Korean Geographical Society
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    • v.44 no.4
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    • pp.544-556
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    • 2009
  • The purpose of this study is to examine the determinant factors of satisfaction and to investigate the difference from clusters in the category of overall state of satisfaction, the thought of revisiting, and the intention of recommendation with the case of Wando Changpogo Festival. Changpogo Festival has been held since 1996 with the theme of 'Changpogo', gained great acknowledgment from television drama, 'Haeshin', and this year of 2009 is its fourteenth. The study analyzed questionnaire which is made up of items on satisfaction factors of 18 local festival visitors. Results from factor analysis are 1) the contents and the souvenir of the festival, 2) work for publicity, 3) tour for near place and convenient facilities. Likewise, results from cluster analysis are 1) a cluster of the contents and the souvenir of the festival, 2) a cluster of tour for near place and convenient facilities, 3) a cluster of work for publicity. In conclusion, there are similar degrees in difference between clusters, but especially the 'tour for near place and convenient facilities' factor has higher score than the others. Therefore, this factor should be cared with great importance.