• 제목/요약/키워드: user preferences

검색결과 501건 처리시간 0.026초

협동적 필터링을 이용한 K-최근접 이웃 수강 과목 추천 시스템 (K-Nearest Neighbor Course Recommender System using Collaborative Filtering)

  • 손기락;김소현
    • 정보교육학회논문지
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    • 제11권3호
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    • pp.281-288
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    • 2007
  • 협동적 필터링은 사용자가 좋아할 만한 항목을 예측하기 위하여 비슷한 선호도를 가지는 다른 사람들의 평가 항목에 근거하여 추천하는 방법이다. 이러한 협동적 필터링 기법은 오늘날과 같이 대규모의 정보가 효과적으로 축적되고 이용 가능하게 된 정보화된 사회에서는 현명한 의사결정을 하도록 도와주는 역할을 한다. 본 논문에서는 대학생들이 수강과목의 취사선택을 용이하게 할 수 있도록 수강과목 추천 시스템을 설계하고 구현하였으며 실험적으로 평가하였다. 먼저, 학생들은 과거 자신이 수강하였던 과목에 대한 과목 선호도를 데이터베이스에 입력한다. 과목 선호도의 패턴이 유사한 학생들은 유사 그룹으로 간주된다. 성향이 유사한 사용자를 찾기 위해 일반적으로 사용되고 있는 피어슨 상관계수에 의한 유사도를 이용하였다. 수강 과목을 예측하려는 학생과 가장 유사한 패턴을 보이는 K 명의 학생들의 수강 과목에서 가장 높은 선호도를 보이는 과목들의 순서화된 리스트를 추천 과목으로 제시한다. 설문 조사를 통한 실험 데이터를 이용하였으며 평균 절대 에러를 사용하여 제안한 방법의 정확도를 평가하였다.

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모델기반 사용자 인터페이스 모델에 관한 연구 (A study on Model-based user interface modules)

  • 주강;김태승;김성한;이승윤;정회경
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2012년도 추계학술대회
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    • pp.709-711
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    • 2012
  • 사용자 인터페이스 기술은 사용자의 선택에 따른 UI를 적용할 수 있는 기술로 최근 사용자 편리를 위한 인터페이스에 대한 연구가 이루어지고 있다. 이를 위해 W3C에서도 다양한 디바이스 환경에서 N-스크린 서비스, 일관된 서비스 제공 및 사용자의 선호도에 따른 UI 적응 서비스를 지원하기 위한 다양한 연구가 진행 중에 있다. 이에 본 논문에서는 사용자의 편의를 위한 UI를 개발하는 데 있어 기본적인 모델 기반의 사용자 인터페이스 기술에 대해 연구하였다. 이는 웹 응용 어플리케이션 적용 방안 기술 확보 및 차세대 웹 어플리케이션을 적용하는데 활용될 것이다.

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현대 공간디자인에 있어 사용자 참여디자인의 의의와 유형에 관한 연구 (A Study on the Significance and the Types of User's Participation in Space Design)

  • 이정민;홍의택
    • 한국실내디자인학회논문집
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    • 제15권6호
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    • pp.89-100
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    • 2006
  • This paper researched social, cultural background, psychological bases, design method and design types with regard to user's participation in space design. This issue of user's participation became one of major paradigms of 21st century not only for space design but also for every other cultural phenomenon. First chapter is an introduction. Second chapter tried to assert the fact that user's participation will be the important aspect for future space design by proving the correlation between user's participation in space design and the important social changes. It also tried to prove the psychological reasons why the users' participations affect the level of user satisfaction. It can be explained by Behaviorism which insisted that our outer behaviors affect our inner attitudes and preferences. Third chapter explained the affordances in design which works as a means of inducing user's participatory behaviors. Fourth chapter proposed the types of participatory space designs classified by the users' behavioral features and their characteristics, intending that they will verify the realization of the theories which we discussed in the former chapters regarding the users' participation in space design. The fifth chapter is a conclusion which says that outwardly, those participations are simply making external changes in design. but actually, they are reflecting more profound social changes and making important psychological effects on users.

다속성 효용이론을 활용한 중국시장에서의 인터넷 의료정보 서비스 선호속성 분석 (An Analysis of Consumer Preferences for Internet Medical Information Service in China Using the Multi-Attribute Utility Theory)

  • 김경환;장영일
    • Journal of Information Technology Applications and Management
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    • 제16권4호
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    • pp.93-107
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    • 2009
  • This study investigated consumer preferences for Internet medical information service in China using the multi-attribute utility theory. The multi-attribute utility theory is a compositional approach for modeling consumer preferences wherein researchers calculate the overall service utility by summing up the evaluation results for each attribute. We found that Chinese Internet medical information users consider the availability of information and quick response to be the most important attributes. Further, they think that the comment feature is less important as compared to other attributes such as costs and updates. In addition, we found that the Internet users having more Internet experience consider these attributes to be more important as compared to the people who are just beginning to surf the Internet. For any successful Internet business, Internet marketers should assess individual-level preference and accordingly organize a fresh campaign. As of now, Internet marketers need estimation methods to predict the market performance of new services in many different business environments. We believe that the multi-attribute utility theory is a useful approach in this regard.

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A Regularity-Based Preprocessing Method for Collaborative Recommender Systems

  • Toledo, Raciel Yera;Mota, Yaile Caballero;Borroto, Milton Garcia
    • Journal of Information Processing Systems
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    • 제9권3호
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    • pp.435-460
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    • 2013
  • Recommender systems are popular applications that help users to identify items that they could be interested in. A recent research area on recommender systems focuses on detecting several kinds of inconsistencies associated with the user preferences. However, the majority of previous works in this direction just process anomalies that are intentionally introduced by users. In contrast, this paper is centered on finding the way to remove non-malicious anomalies, specifically in collaborative filtering systems. A review of the state-of-the-art in this field shows that no previous work has been carried out for recommendation systems and general data mining scenarios, to exactly perform this preprocessing task. More specifically, in this paper we propose a method that is based on the extraction of knowledge from the dataset in the form of rating regularities (similar to frequent patterns), and their use in order to remove anomalous preferences provided by users. Experiments show that the application of the procedure as a preprocessing step improves the performance of a data-mining task associated with the recommendation and also effectively detects the anomalous preferences.

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.

프라이버시 보호 상황인식 시스템 개발을 위한 쌍방향 P3P 방법론 (A Mutual P3P Methodology for Privacy Preserving Context-Aware Systems Development)

  • 권오병
    • Asia pacific journal of information systems
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    • 제18권1호
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    • pp.145-162
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    • 2008
  • One of the big concerns in e-society is privacy issue. In special, in developing robust ubiquitous smart space and corresponding services, user profile and preference are collected by the service providers. Privacy issue would be more critical in context-aware services simply because most of the context data themselves are private information: user's current location, current schedule, friends nearby and even her/his health data. To realize the potential of ubiquitous smart space, the systems embedded in the space should corporate personal privacy preferences. When the users invoke a set of services, they are asked to allow the service providers or smart space to make use of personal information which is related to privacy concerns. For this reason, the users unhappily provide the personal information or even deny to get served. On the other side, service provider needs personal information as rich as possible with minimal personal information to discern royal and trustworthy customers and those who are not. It would be desirable to enlarge the allowable personal information complying with the service provider's request, whereas minimizing service provider's requiring personal information which is not allowed to be submitted and user's submitting information which is of no value to the service provider. In special, if any personal information required by the service provider is not allowed, service will not be provided to the user. P3P (Platform for Privacy Preferences) has been regarded as one of the promising alternatives to preserve the personal information in the course of electronic transactions. However, P3P mainly focuses on preserving the buyers' personal information. From time to time, the service provider's business data should be protected from the unintended usage from the buyers. Moreover, even though the user's privacy preference could depend on the context happened to the user, legacy P3P does not handle the contextual change of privacy preferences. Hence, the purpose of this paper is to propose a mutual P3P-based negotiation mechanism. To do so, service provider's privacy concern is considered as well as the users'. User's privacy policy on the service provider's information also should be informed to the service providers before the service begins. Second, privacy policy is contextually designed according to the user's current context because the nomadic user's privacy concern structure may be altered contextually. Hence, the methodology includes mutual privacy policy and personalization. Overall framework of the mechanism and new code of ethics is described in section 2. Pervasive platform for mutual P3P considers user type and context field, which involves current activity, location, social context, objects nearby and physical environments. Our mutual P3P includes the privacy preference not only for the buyers but also the sellers, that is, service providers. Negotiation methodology for mutual P3P is proposed in section 3. Based on the fact that privacy concern occurs when there are needs for information access and at the same time those for information hiding. Our mechanism was implemented based on an actual shopping mall to increase the feasibility of the idea proposed in this paper. A shopping service is assumed as a context-aware service, and data groups for the service are enumerated. The privacy policy for each data group is represented as APPEL format. To examine the performance of the example service, in section 4, simulation approach is adopted in this paper. For the simulation, five data elements are considered: $\cdot$ UserID $\cdot$ User preference $\cdot$ Phone number $\cdot$ Home address $\cdot$ Product information $\cdot$ Service profile. For the negotiation, reputation is selected as a strategic value. Then the following cases are compared: $\cdot$ Legacy P3P is considered $\cdot$ Mutual P3P is considered without strategic value $\cdot$ Mutual P3P is considered with strategic value. The simulation results show that mutual P3P outperforms legacy P3P. Moreover, we could conclude that when mutual P3P is considered with strategic value, performance was better than that of mutual P3P is considered without strategic value in terms of service safety.

협업 필터링을 이용한 순위 정렬 모델 기반 (IP)TV 프로그램 자동 추천 (Automatic Recommendation of (IP)TV programs based on A Rank Model using Collaborative Filtering)

  • 김은희;표신지;김문철
    • 방송공학회논문지
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    • 제14권2호
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    • pp.238-252
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    • 2009
  • 방송과 융합의 시대로 접어들면서 (IP)TV 단말에서 이용 가능한 프로그램 콘텐츠 수가 급격히 증가 하였다. 이로 인해, 사용자 (시청자)가 선호하는 방송 프로그램 콘텐츠로의 접근성이 주요한 사항이 되었다. 본 논문은 유사 사용자 선호도에 기반을 둔 협업 필터링을 이용하여(IP)TV 프로그램을 효율적으로 사용자에게 자동 추천하는 연구에 관한 내용이다. 개인의 시청 프로그램 선호도를 고려하여 방송 프로그램을 추천하기 위해서, 제안하는 추천 시스템의 구성은 오프라인과 온라인 연산으로 구성된다. 오프라인 연산과정에서 (IP)TV 프로그램, 장르, 채널에 대한 개인의 선호도를 묵시적으로 추론 하는 방법을 제시하고, 동적 퍼지 클러스터링 방법을 사용하여 각 개인의 선호도에 따라 사용자들을 그룹 짓되, 특징 벡터를 장르와 채널에 대한 선호도로 결합하여 사용하는 방법을 제시한다. 또한, (IP)TV 단말에 로그인 한 활동 사용자에게, 높은 정확도로 선호 프로그램을 추천하기 위해서, 활동 사용자와 관심 시청 프로그램이 유사한 사용자들을 유사도 측정 방법을 사용하여 한 번 더 추출하고, 이 추출된 유사 취향 사용자들의 선호 (IP)TV 프로그램들에 대해, EPG를 이용하여 현재 방송되지 않는 프로그램들을 제외시킨다. 마지막 단계에서는 추천 후보 프로그램들에 대해 본 논문에서 제안하는 순위 정렬 모델을 이용하여 추천 우선순위를 결정하여 제시한다. 특별히, 본 논문은 BM(Best Match) 알고리즘을 확장하여 개인 선호도를 고려한 순위 정렬 모델을 제시한다. 실험을 통해, 본 논문에서 제안한 프로그램 자동 추천 알고리듬은 2,441명의 사용자에 대해 5개의 프로그램을 추천하였을 경우, 62.1%의 예측 정확도를 나타내었다.

도서 정보 및 본문 텍스트 통합 마이닝 기반 사용자 맞춤형 도서 큐레이션 시스템 (Personalized Book Curation System based on Integrated Mining of Book Details and Body Texts)

  • 안희정;김기원;김승훈
    • Journal of Information Technology Applications and Management
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    • 제24권1호
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    • pp.33-43
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    • 2017
  • The content curation service through big data analysis is receiving great attention in various content fields, such as film, game, music, and book. This service recommends personalized contents to the corresponding user based on user's preferences. The existing book curation systems recommended books to users by using bibliographic citation, user profile or user log data. However, these systems are difficult to recommend books related to character names or spatio-temporal information in text contents. Therefore, in this paper, we suggest a personalized book curation system based on integrated mining of a book. The proposed system consists of mining system, recommendation system, and visualization system. The mining system analyzes book text, user information or profile, and SNS data. The recommendation system recommends personalized books for users based on the analysed data in the mining system. This system can recommend related books using based on book keywords even if there is no user information like new customer. The visualization system visualizes book bibliographic information, mining data such as keyword, characters, character relations, and book recommendation results. In addition, this paper also includes the design and implementation of the proposed mining and recommendation module in the system. The proposed system is expected to broaden users' selection of books and encourage balanced consumption of book contents.

An Auto Playlist Generation System with One Seed Song

  • Bang, Sung-Woo;Jung, Hye-Wuk;Kim, Jae-Kwang;Lee, Jee-Hyong
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제10권1호
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    • pp.19-24
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    • 2010
  • The rise of music resources has led to a parallel rise in the need to manage thousands of songs on user devices. So users have a tendency to build playlist for manage songs. However the manual selection of songs for creating playlist is a troublesome work. This paper proposes an auto playlist generation system considering user context of use and preferences. This system has two separated systems; 1) the mood and emotion classification system and 2) the music recommendation system. Firstly, users need to choose just one seed song for reflecting their context of use. Then system recommends candidate song list before the current song ends in order to fill up user playlist. User also can remove unsatisfied songs from the recommended song list to adapt the user preference model on the system for the next song list. The generated playlists show well defined mood and emotion of music and provide songs that the preference of the current user is reflected.