• Title/Summary/Keyword: 이용자추천정보

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A Study on Mapping Users' Topic Interest for Question Routing for Community-based Q&A Service (커뮤니티 기반 Q&A서비스에서의 질의 할당을 위한 이용자의 관심 토픽 분석에 관한 연구)

  • Park, Jong Do
    • Journal of the Korean Society for information Management
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    • v.32 no.3
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    • pp.397-412
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    • 2015
  • The main goal of this study is to investigate how to route a question to some relevant users who have interest in the topic of the question based on users' topic interest. In order to assess users' topic interest, archived question-answer pairs in the community were used to identify latent topics in the chosen categories using LDA. Then, these topic models were used to identify users' topic interest. Furthermore, the topics of newly submitted questions were analyzed using the topic models in order to recommend relevant answerers to the question. This study introduces the process of topic modeling to investigate relevant users based on their topic interest.

Influence A Study on the Effects of Personalized Recommendation Service of OTT Service on the Relationship Strength and Customer Loyalty in Accordance with Type of Contents (콘텐츠 유형에 따라 OTT 서비스의 개인화추천서비스가 관계강화 및 고객충성도에 미치는 영향)

  • Kim, Minjoo;Kim, Minkyun
    • Journal of Service Research and Studies
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    • v.8 no.4
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    • pp.31-51
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    • 2018
  • The objective of this study is to suggest the measures for providing the personalized recommendation service, by analyzing the effects of personalized recommendation service of OTT service on the relationship strength and customer loyalty, and also to verify the differences in meanings of personalized recommendation service in accordance with the type of contents. In the results of this study, the personalized recommendation service has significant effects on the customer loyalty with the mediation of relationship strength, and in accordance with the type of contents mainly used by customers, there are differences in the effects of personalized recommendation service on the customers. Personalized recommendation service could be used as a tool for strengthening the relationship by inducing the commitment, which could improve the customer loyalty. When the contents have more active communications with customers, personalized recommendation service could largely contribute to the improvement of loyalty.

Analysis of Instagram Use in Public Libraries and Policy Implications (공공도서관의 인스타그램 게시물 이용 분석과 정책적 시사점)

  • Dahyung Choi;Eungyung Park
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.35 no.2
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    • pp.65-84
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    • 2024
  • As the number of Instagram users continues to grow, an increasing number of public libraries are establishing and maintaining accounts on the Instagram platform. The objective of this study is to classify and analyze the content of Instagram posts from 14 public libraries that are actively engaged on the platform. A classification of post types, divided into seven large, 16 medium, and 76 small categories, was employed to analyze the content of posts on each library's Instagram account from the account's inception to the end of December 2023. The analysis revealed that library posts focused on a few items, including book recommendations, library introductions and news, and event announcements of literary and arts programs. Program event announcements and reviews, book recommendations and reading programs were found to be highly correlated with user engagement and teen reading programs. Based on these findings, it is recommended that future Instagram posts should be more user-centered and interactive, and that libraries should actively promote their events on Instagram and other social media platforms.

A Study of the Intelligent Researcher Connection Network Build-up that Merges the Recommendation System and Social Network (추천시스템과 소셜 네트워크를 융합한 지능형 연구자연결망 구축)

  • Lee, Choong-Moo;Lee, Sang-Gi;Lee, Byeong-Seop
    • Journal of Information Management
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    • v.40 no.1
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    • pp.199-215
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    • 2009
  • The web 2.0 concept rapidly spreads to the various field which is based on an opening, the participation, and a share. And the research about the recommendation system, that is the personalize feature, and social network is very active. In the case of the recommendation system and social network, it had been developing in the respectively different area and the new research toward the service model of a form that it fuses these is insignificant. In this paper, I'm going to introduce efficient social network which is called the researcher connection network. It is possible to recommend the researcher intellectually who studies the similar field by analyzing the usage log and user profile. Through this study, we could solved the network expandability problem which is due to the user passive participation and the difficulty of the initial network construction that is the conventional social network problem.

A Study on the Current State of the Library's AI Service and the Service Provision Plan (도서관의 인공지능(AI) 서비스 현황 및 서비스 제공 방안에 관한 연구)

  • Kwak, Woojung;Noh, Younghee
    • Journal of Korean Library and Information Science Society
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    • v.52 no.1
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    • pp.155-178
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    • 2021
  • In the era of the 4th industrial revolution, public libraries need a strategy for promoting intelligent library services in order to actively respond to changes in the external environment such as artificial intelligence. Therefore, in this study, based on the concept of artificial intelligence and analysis of domestic and foreign artificial intelligence related trends, policies, and cases, we proposed the future direction of introduction and development of artificial intelligence services in the library. Currently, the library operates a reference information service that automatically provides answers through the introduction of artificial intelligence technologies such as deep learning and natural language processing, and develops a big data-based AI book recommendation and automatic book inspection system to increase business utilization and provide customized services for users. Has been provided. In the field of companies and industries, regardless of domestic and overseas, we are developing and servicing technologies based on autonomous driving using artificial intelligence, personal customization, etc., and providing optimal results by self-learning information using deep learning. It is developed in the form of an equation. Accordingly, in the future, libraries will utilize artificial intelligence to recommend personalized books based on the user's usage records, recommend reading and culture programs, and introduce real-time delivery services through transport methods such as autonomous drones and cars in the case of book delivery service. Service development should be promoted.

Comparative Study of Discovery Services (디스커버리 서비스의 비교 분석)

  • Kwak, Seung-Jin;Shin, Jae-Min;Kim, Bo-Young
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.27 no.4
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    • pp.5-20
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    • 2016
  • Discovery service has as its object to cope with the user to take advantage of the collection of the library as possible to index and search, one step further, the interface by more efficiently to the user's information needs. Discovery service has features such as providing a ranking and navigation services to subdivide the search results by facet results along the suitability and visually rich display, suggestions, recommendations associated resources. In this study introduces the status of discovery services such as discovery service products, usage status, and features, and compares and analyzes the use agencies, content status, main functions, and features of the three discovery services used in Korea library.

A Study on the Method of Scholarly Paper Recommendation Using Multidimensional Metadata Space (다차원 메타데이터 공간을 활용한 학술 문헌 추천기법 연구)

  • Miah Kam;Jee Yeon Lee
    • Journal of the Korean Society for information Management
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    • v.40 no.1
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    • pp.121-148
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    • 2023
  • The purpose of this study is to propose a scholarly paper recommendation system based on metadata attribute similarity with excellent performance. This study suggests a scholarly paper recommendation method that combines techniques from two sub-fields of Library and Information Science, namely metadata use in Information Organization and co-citation analysis, author bibliographic coupling, co-occurrence frequency, and cosine similarity in Bibliometrics. To conduct experiments, a total of 9,643 paper metadata related to "inequality" and "divide" were collected and refined to derive relative coordinate values between author, keyword, and title attributes using cosine similarity. The study then conducted experiments to select weight conditions and dimension numbers that resulted in a good performance. The results were presented and evaluated by users, and based on this, the study conducted discussions centered on the research questions through reference node and recommendation combination characteristic analysis, conjoint analysis, and results from comparative analysis. Overall, the study showed that the performance was excellent when author-related attributes were used alone or in combination with title-related attributes. If the technique proposed in this study is utilized and a wide range of samples are secured, it could help improve the performance of recommendation techniques not only in the field of literature recommendation in information services but also in various other fields in society.

AHP-Based Recommendation System of Mobile Games Reflecting User Preferences (사용자 선호도를 반영한 AHP 기반 모바일 게임 추천 시스템)

  • Oh, Jae-Taek;Lee, Sang-Yong
    • Journal of Digital Convergence
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    • v.15 no.1
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    • pp.427-433
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    • 2017
  • Mobile game users tend to value the opinions from their friends or SNS when making a decision on which game to play. This is because they are not satisfied with the information on suggestions provided by the conventional mobile game recommendation systems. In this research, we made a system that can reflect user preference directly by using Analytic Hierarchy Process(AHP). In the system, the hierarchy of AHP is composed of final goal(Level 1), evaluation basis(Level 2) and alternative(Level 3). And the system is made up of an input module, an AHP processing module, a recommendation module and database. Through comparison analysis with two conventional systems to test the performance of the system, we could find that the system got more higher satisfaction than the other systems.

A Study on the Development of the School Library Book Recommendation System Using the Association Rule (연관규칙을 활용한 학교도서관 도서추천시스템 개발에 관한 연구)

  • Lim, Jeong-Hoon;Cho, Changje;Kim, Jongheon
    • Journal of the Korean Society for information Management
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    • v.39 no.3
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    • pp.1-22
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    • 2022
  • The purpose of this study is to propose a book recommendation system that can be used in school libraries. The book recommendation system applies an algorithm based on association rules using DLS lending data and is designed to provide personalized book recommendation services to school library users. For this purpose, association rules based on the Apriori algorithm and betweenness centrality analysis were applied and detailed functions such as descriptive statistics, generation of association rules, student-centered recommendation, and book-centered recommendation were materialized. Subsequently, opinions on the use of the book recommendation system were investigated through in-depth interviews with teacher librarians. As a result of the investigation, opinions on the necessity and difficulty of book recommendation, student responses, differences from existing recommendation methods, utilization methods, and improvements were confirmed and based on this, the following discussions were proposed. First, it is necessary to provide long-term lending data to understand the characteristics of each school. Second, it is necessary to discuss the data integration plan by region or school characteristics. Third, It is necessary to establish a book recommendation system provided by the Comprehensive Support System for Reading Education. Based on the contents proposed in this study, it is expected that various discussions will be made on the application of a personalization recommendation system that can be used in the school library in the future.

Implementation of Recommender System of Seoul Urban Parks Using Rule-based Expert System based on PROLOG (PROLOG기반의 규칙 기반 전문가 시스템을 이용한 서울시 도시 공원 추천 시스템 구현)

  • Son, Se-Jin;Kim, Da-Hee;Cho, Ye-Bon;Chun, Soo-Wan;Lee, Kang-Hee
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.7 no.7
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    • pp.847-856
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    • 2017
  • In this paper, we propose a system to users which recommends suitable park using linguistic objects by rule-based inference engine which is made with Prolog. According to the function of city park, which provides positive elements to people such as social, psychological, environmental, and physical, Seoul city park is classified into 6 categories. The classified parks are recommended to users based on the rule based expert system. Rule-based object of park recommendation designs nine linguistic objects based on activity, multi-purposiveness, accessibility, and usage of time. This assigns allowed value accordingly. Generated rules by using these values are fired by user's preference, and infer recommended park. Information on preferences is obtained by way of dialogue, in which the user is asked questions about the three elements that are the criteria for choosing a park. As a result, through the park recommendation system, we intend to increase the user's satisfaction of using park and leisure activities.