• Title/Summary/Keyword: collaborative information behavior model

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A Study on Mariners' Standard Behavior for Collision Avoidance (3) - Modeling of the execution process of an avoiding action based on human factors -

  • Park, Jung-Sun;Kobayashi, Hiroaki;Yea, Byeong-Deok
    • Journal of Navigation and Port Research
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    • v.32 no.4
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    • pp.279-285
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    • 2008
  • We have proposed modeling methods of mariners' standard behavior for collision avoidance by analyzing mariners' recognition process in a previous study. As a subsequent study, the aim of this study is to build a model of mariners' execution process which is one of six processes in the condition of collision avoidance. In this study, thus, the structure of mariners' information processing on the process of taking avoiding actions is described and the relation between mariners' behavior and necessary factors in the process is analyzed. And then we have built a model of mariners' standard behavior for execution process based on the characteristics of mariners in ship-handling, which are obtained from the international collaborative research on human factors. It is tried to define the contents of execution process based on the standard behavior of mariners for collision avoidance and to formulate information processing of mariners.

Student-, School-, and ICT-Factors Predicting Computer-based Collaborative Problem Solving: Focusing on Analyses of Multi-level Models (컴퓨터 기반의 협력적 문제해결력 성취를 예측하는 학생과 학교 및 ICT 요인 : 다층모형 분석을 중심으로)

  • Lim, Hyo Jin;Lee, Soon Young
    • Journal of The Korean Association of Information Education
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    • v.22 no.4
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    • pp.457-471
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    • 2018
  • This study examined student- and school-level background and ICT factors that affected PISA 2015 Collaborative Problem Solving (CPS) for Korean students (4863 students from 142 high schools). A two-level hierarchical linear model (HLM) was analyzed from the basic model (model 1) with no predictors to the final model (model 5) with all predictors. Results showed that first, gender, socioeconomic/cultural backgrounds, cooperation level positively predicted CPS scores while perceived unfairness of teacher negatively predicted the outcome. Second, the more frequently ICT was used for out-of-school learning purposes, the less frequently ICT was used for entertainment purposes, and the less frequently ICT was used in schools, the higher CPS scores were. Considering ICT autonomy and social interaction variables measured for the first time in PISA 2015, students who were more interested in ICT and more autonomous in using ICT devices achieved higher CPS scores. On the other hand, the more students considered ICT important as social interaction, the less they gained CPS scores. Third, in terms of school-level characteristics, the smaller the students behavior detrimental to learning, the higher the teachers perceived positive working environment, and the fewer the number of computers available per student, the higher CPS scores were. To facilitate computer-based collaborative problem-solving competence, it is important for students to have interest and autonomy in using ICT. In addition, the guidelines of ICT use and SW curriculum need to be established in order to increase the effectiveness of using ICT device in school.

(Efficient Methods for Combining User and Article Models for Collaborative Recommendation) (협력적 추천을 위한 사용자와 항목 모델의 효율적인 통합 방법)

  • 도영아;김종수;류정우;김명원
    • Journal of KIISE:Software and Applications
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    • v.30 no.5_6
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    • pp.540-549
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    • 2003
  • In collaborative recommendation two models are generally used: the user model and the article model. A user model learns correlation between users preferences and recommends an article based on other users preferences for the article. Similarly, an article model learns correlation between preferences for articles and recommends an article based on the target user's preference for other articles. In this paper, we investigates various combination methods of the user model and the article model for better recommendation performance. They include simple sequential and parallel methods, perceptron, multi-layer perceptron, fuzzy rules, and BKS. We adopt the multi-layer perceptron for training each of the user and article models. The multi-layer perceptron has several advantages over other methods such as the nearest neighbor method and the association rule method. It can learn weights between correlated items and it can handle easily both of symbolic and numeric data. The combined models outperform any of the basic models and our experiments show that the multi-layer perceptron is the most efficient combination method among them.

A Design of Web-based Agent Model for Global Supply Chain Management (국제적 공급사슬 관리를 위한 웹기반 에이전트모형 설계)

  • Lee, Ho-Chang;Kim, Min-Yong
    • Asia pacific journal of information systems
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    • v.10 no.2
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    • pp.23-49
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    • 2000
  • We proposed a conceptual design of the web-based agent model for global supply chain management(GSCM), where agents representing autonomous operational units, such as suppliers, factories, distribution center and customers, cooperate and are coordinated through the information exchange. The agent model assumed the hierarchical federated system. In the federated system, the agents of the same region are grouped and linked to the region-specific facilitator only through which communication between agents is allowed. The facilitator is responsible for monitoring and controlling the conversations consisting of the message flows across the agents. A web-based user presentation was also designed so that human users could involve in collaborative settings into the GSCM multi-agent system. In the conversation protocols which allow for complex coordinated behavior among agents, the KQML was extended to represent the messages. A GSCM scenario where the supply chain is formed upon customer order and supply decision is made was used to demonstrate the dynamics of the conversation protocols.

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Hybrid Movie Recommendation System Using Clustering Technique (클러스터링 기법을 이용한 하이브리드 영화 추천 시스템)

  • Sophort Siet;Sony Peng;Yixuan Yang;Sadriddinov Ilkhomjon;DaeYoung Kim;Doo-Soon Park
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.05a
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    • pp.357-359
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    • 2023
  • This paper proposes a hybrid recommendation system (RS) model that overcomes the limitations of traditional approaches such as data sparsity, cold start, and scalability by combining collaborative filtering and context-aware techniques. The objective of this model is to enhance the accuracy of recommendations and provide personalized suggestions by leveraging the strengths of collaborative filtering and incorporating user context features to capture their preferences and behavior more effectively. The approach utilizes a novel method that combines contextual attributes with the original user-item rating matrix of CF-based algorithms. Furthermore, we integrate k-mean++ clustering to group users with similar preferences and finally recommend items that have highly rated by other users in the same cluster. The process of partitioning is the use of the rating matrix into clusters based on contextual information offers several advantages. First, it bypasses of the computations over the entire data, reducing runtime and improving scalability. Second, the partitioned clusters hold similar ratings, which can produce greater impacts on each other, leading to more accurate recommendations and providing flexibility in the clustering process. keywords: Context-aware Recommendation, Collaborative Filtering, Kmean++ Clustering.

A Multi-agent Architecture for Coordination of Supply Chains with Local Information Sharing (지역적 정보 공유를 활용하는 멀티 에이전트 시스템 기반의 공급사슬 관리 아키텍쳐)

  • Ahn, Hyung-Jun;Park, Sung-Joo
    • Asia pacific journal of information systems
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    • v.14 no.4
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    • pp.49-70
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    • 2004
  • Multi-agent technology is being regarded as one of the promising technologies for today's supply chain management because of its desirable features such as autonomy, intelligence, and collaboration. This paper suggests a multi-agent system architecture with which companies can improve the efficiency of their supply chains by collaborative operation. Reflecting the practical difficulties of collaboration in complex supply chains, the architecture allows agent systems to share information with only neighboring companies for the coordinated operation. The suggested architecture is elaborated with a collaboration model based on Petri-net, conversation models for communication, and internal behavior models of each agent. A simulation experiment was performed for the evaluation of the suggested architecture. The result implies that when the estimation of market demand is higher than a certain level, the suggested architecture can be beneficial.

A Study on the Reading Effectiveness by Collaborative Reading Practice of Teenagers (청소년의 자율 협력적 독서실행에 따른 독서유효성 효과 연구)

  • Kim, Myung-Hee;Cho, Hyun-Yang
    • Journal of Korean Library and Information Science Society
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    • v.49 no.2
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    • pp.79-104
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    • 2018
  • This study was to present a model of cooperative reading practice and verify reading effectiveness on youth. For this purpose, 68 reading clubs were established in 61 districts and 8 high schools. The research groups were classified as the poor reading group, the good reading group, and the mixed-skill reading group. The cooperative reading groups were carried out for four months. We developed a questionnaire on Reading effectiveness conducted it pre- and post-test, and analyzed the results through the SPSS statistical program. We found that there was a positive change in the reading effectiveness of youth and overall-the highest effectiveness was found in the poor reading group. In addition, there was a positive change in the reading behavior of youth. The change of reading effectiveness was found to affect reading behavior.

A Scalable Multicasting with Group Mobility Support in Mobile Ad Hoc Networks

  • Kim, Kap-Dong;Lee, Kwang-Il;Park, Jun-Hee;Kim, Sang-Ha
    • Journal of Information Processing Systems
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    • v.3 no.1
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    • pp.1-7
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    • 2007
  • In mobile ad hoc networks, an application scenario requires mostly collaborative mobility behavior. The key problem of those applications is scalability with regard to the number of multicast members as well as the number of the multicast group. To enhance scalability with group mobility, we have proposed a multicast protocol based on a new framework for hierarchical multicasting that is suitable for the group mobility model in MANET. The key design goal of this protocol is to solve the problem of reflecting the node's mobility in the overlay multicast tree, the efficient data delivery within the sub-group with group mobility support, and the scalability problem for the large multicast group size. The results obtained through simulations show that our approach supports scalability and efficient data transmission utilizing the characteristic of group mobility.

Improvement of a Product Recommendation Model using Customers' Search Patterns and Product Details

  • Lee, Yunju;Lee, Jaejun;Ahn, Hyunchul
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.1
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    • pp.265-274
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    • 2021
  • In this paper, we propose a novel recommendation model based on Doc2vec using search keywords and product details. Until now, a lot of prior studies on recommender systems have proposed collaborative filtering (CF) as the main algorithm for recommendation, which uses only structured input data such as customers' purchase history or ratings. However, the use of unstructured data like online customer review in CF may lead to better recommendation. Under this background, we propose to use search keyword data and product detail information, which are seldom used in previous studies, for product recommendation. The proposed model makes recommendation by using CF which simultaneously considers ratings, search keywords and detailed information of the products purchased by customers. To extract quantitative patterns from these unstructured data, Doc2vec is applied. As a result of the experiment, the proposed model was found to outperform the conventional recommendation model. In addition, it was confirmed that search keywords and product details had a significant effect on recommendation. This study has academic significance in that it tries to apply the customers' online behavior information to the recommendation system and that it mitigates the cold start problem, which is one of the critical limitations of CF.

An Analysis of Media of Social Studies 1 Textbooks for the Middle School with the Information Processing Model (정보처리모형을 이용한 중학교 『사회 1』 교과서 수록 매체 분석)

  • Song, Gi-Ho
    • Journal of the Korean Society for Library and Information Science
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    • v.53 no.2
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    • pp.5-27
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    • 2019
  • The purpose of this study is to analyze the media of middle school social studies 1 textbooks with the information processing model and to suggest educational information services of teacher librarians under a collaborative Instruction. For this purpose, 1,089 inquiry tasks embedded in 8 types of textbooks for middle school social studies developed under the 2015 revised curriculum were analyzed. The media as an input element was analyzed by the type and the characteristic as a processing element was analyzed by the cognitive behavior types. And the aspect of the output factor of the media utilized the multiple intelligences. As a result of the analysis, the media in the inquiry task solving process mainly consisted of visual media based on photographs and illustrations and general reading materials. The processing method of media is understanding through analysis and inference through structuring. And the output utilized speaking and writing of the language intelligence. Based on the results, it is shown that educational information services that teacher librarians could provide for inquiry activities are composed of developing curriculum map, teaching inquiry processing and skills, and designing work sheets with graphic organizer and multiple intelligences under the information processing steps.