• Title/Summary/Keyword: recommending

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Automated Reviewers Recommendation on Online Submission System in Journal Publishing (국내외 학술지 투고관리시스템의 심사위원 추천 기능 분석)

  • Eun-Ja, Shin
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.33 no.4
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    • pp.139-157
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    • 2022
  • Finding and selecting proper reviewers is a burden on the publisher of the journal. In order to solve this problem, the online submission system started to recommend appropriate reviewers automatically. It includes a variety of new features, from recommending authors in the references of submitted papers as reviewers to finding similar papers by searching the citation index and suggesting reviewer candidates extensively. This study investigated how the online submission system provides functions such as recommendation of reviewers. As a result of examining major online submission systems, ScholarOne and Editorial Manager were recommending reviewer candidates by commercial citation index and review history platform. On the other hand, JAMS, a domestic online submission system, did not have any advanced functions such as recommendation of candidates for reviewers. Sooner or later, in Korea, it seems that more efforts should be made to improve the function of online submission system, such as recommending suitable reviewers for papers.

A Study of Similar Blog Recommendation System Using Termite Colony Algorithm (흰개미 군집 알고리즘을 이용한 유사 블로그 추천 시스템에 관한 연구)

  • Jeong, Gi Sung;Jo, I-Seok;Lee, Malrey
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.13 no.1
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    • pp.83-88
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    • 2013
  • This paper proposes a recommending system of the similar blogs gathered with similarities between blogs according to the similarity, dividing words, for each frequency, that individual blogs have. It improved the algorithm of k-means, using the model of the habits of white ants for better performance of clustering, and showed better performance of clustering as a result of evaluating and comparing with the existing algorithm of k-means as the improved algorithm. The recommending system of similar blog was designed and embodied, using the improved algorithm. TCA can reduce clustering time and the number of moving time for clustering compare with K-means algorithm.

Similarity-based Service Recommendation for Service-Mashup Developers (서비스 매쉬업 개발자를 위한 유사도 기반 서비스 추천 방법)

  • Kim, HyunSeung;Ko, InYoung
    • Journal of KIISE
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    • v.44 no.9
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    • pp.908-917
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    • 2017
  • As web service technologies are widely used, there have been many efforts to develop approaches for recommending appropriate web services to users in complex and dynamic service environments. In addition, for the effective development of service mashups, service recommender systems that are specialized for service composition have been developed. However, existing service recommender systems for service mashups are not effective at recommending services in a personalized manner that reflect developers' preferences. To deal with this issue, we propose an approach that recommends services based on the similarities between mashup developers who have developed similar service mashups. The proposed approach is then evaluated by using the mashup data retrieved from ProgrammableWeb. The evaluation results clearly show that the proposed approach is an effective way of improving service recommendations compared to the traditional user-based collaborative filtering algorithm.

Digital Convergence Teaching Strategy System using Spearman Correlation Coefficients (스피어만 상관계수를 이용한 디지털 융합 강의 전략 시스템)

  • Lee, Byung-Wook
    • Journal of Internet Computing and Services
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    • v.11 no.6
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    • pp.111-122
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    • 2010
  • Since educating digital convergence is to unite various sciences and technologies with computer as the central figure, it has different range and methods of education. Therefore, it has problems with recommending limited conceptual information because of difficulties to standardize education plan and teaching strategies. In this paper, I propose education plan and teaching strategy system by using Spearman correlation coefficients. This system is to find a solution against disadvantage of recommending limited conceptual information by ranking relations of teaching strategies from the information based on the demand of industrial and academic fields, and then provides lists of teaching strategy information suitable for user's atmosphere and characteristics. Performance test is to compare effects of precision and recall with existing service systems. The test shows 90.4% of precision and 77.6% of recall.

Analytical Design Methodology for Recommending VDT Workstation Settings and Computer Accessories Layout

  • Rurkhamet, Busagarin;Nanthavanij, Suebsak
    • Industrial Engineering and Management Systems
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    • v.3 no.2
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    • pp.140-150
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    • 2004
  • Repetitive stress injury at the wrist has been reported as a common injury among visual display terminal (VDT) users (i.e., computer users). Adjusting a VDT workstation (computer table and chair) to maintain a correct seated posture while operating a keyboard is perhaps the most frequently recommended preventive solution. This paper proposes an analytical design methodology based on ergonomic design principles for recommending appropriate VDT workstation settings and layout of individual computer accessories on the computer table. The proposed design methodology consists of two interrelated phases: (1) determination of VDT workstation settings, and (2) design of computer accessories layout. Based on the information about the VDT user, dominant task to be performed, typing skill, and degrees of physical and visual interactions between the user and computer accessories, adjustment and layout solutions are recommended to allow having a correct seated posture while minimizing both physical and visual movements. The results from an experiment show that when adjusting the workstation and locating the computer accessories according to the recommendations given by the proposed design methodology, the user's hand movements can be significantly reduced.

The Effect of Nursing Information on the Women's Emotional Adaptation Undergoing a Hysterectomy (간호정보 제공이 자궁적출술 환자의 수술 후 정서적 적응에 미치는 영향)

  • Chung, Eun-Soon;Jang, Sei-Jung;Hwang, Sun-Kyung
    • Women's Health Nursing
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    • v.8 no.3
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    • pp.380-388
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    • 2002
  • The purpose of this Quasi-experimental design was to assess the effects of a hysterectomy on women's emotional response and ultimately, to develop a nursing protocol recommending nursing education for women undergoing a hysterectomy. The subjects at D university hospital receiving a hysterectomy,(for benign gynecological disease) were invited to participate in the study. Subjects who agreed to participate were allocated into control or experimental groups. Each group consisted of 30 women. The subjects emotional adaptation was surveyed through mood questionnaires. The data were analyzed using SAS program. The findings of the study are as follows: In the post test, the "experimental group" reported higher emotional adaptation than the "control group". Between pre and post testing, the "experimental group" showed significant improvement in emotional response; the "control group" did not. In conclusion, allocating nursing information to women both before and after undergoing a hysterectomy was confirmed as an effective nursing intervention for promoting women's emotional adaptation. Therefore, we propose a nursing protocol should be adapted recommending nursing education for women undergoing a hysterectomy.

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The Influence of Social Presence on Evaluating Personalized Recommender Systems

  • Choi, Jae-Won;Lee, Hong-Joo;Kim, Yong-Chul
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2008.10a
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    • pp.410-414
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    • 2008
  • Providing recommendations is acknowledged as one of important features of a business-to-consumer online storefront. Though there have been many studies on algorithms and operational procedures of personalized recommender systems, there is still a lack of empirical evidence demonstrating relationships between social presence and two important outcome variables of recommender systems: reuse intention and trust. To test the existence of a causal link between social presence and reuse intention, and mediating role of trust between these two variables, this study performed experiments varying level of social presence while providing personalized recommendations to users based on their explicit preferences. This study also compared these effects in two different product contexts: hedonic and utilitarian product. The results show that the provision of higher social presence increases both the reuse intention and trust of the recommender systems. In addition, the influence of social presence on reuse intention in the setting of recommending utilitarian products is less than that in the setting of recommending hedonic products.

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A Method for Converting OSEM to OWL and Recommending Interest Blog Communities (온톨로지 기반 시맨틱 블로그 모델의 OWL 변환 및 관심 블로그 커뮤니티 추천 기법)

  • Xu, Rong-Hua;Yang, Kyung-Ah;Yang, Jae-Dong;Choi, Wan
    • Journal of KIISE:Computing Practices and Letters
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    • v.15 no.5
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    • pp.385-389
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    • 2009
  • As a new community forming environment, the blog platform enables sharing of the resources in blogosphere through active information exchange. Many researches have been performed to recommend appropriate resources to users from vast amounts of blog resources. As one of the solutions OSEM defines the knowledge base in the blogosphere with ontology for effectively modeling it. In this paper, we propose a technique of converting the knowledge base into the OWL ontology for sharing it on the semantic web environment. An inference method is then applied to the OWL ontology for recommending interest blog communities. For this aim, a mapping method is offered and then SWRL inference and SPARQL query based on the ontology are employed to extract interest blog communities.

Identifying Prospective Visitors and Recommending Personalized Booths in the Exhibition Industry

  • Moon, Hyun Sil;Kim, Jae Kyeong;Choi, Il Young
    • Journal of Information Technology Applications and Management
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    • v.21 no.1
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    • pp.85-105
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    • 2014
  • Exhibition industry is important business domains to many countries. Not only lots of countries designated the exhibition industry as tools to stimulate national economics, but also many companies offer millions of service or products to customers. Recommender systems can help visitors navigate through large information spaces of various booths. However, no study before has proposed a methodology for identifying and acquiring prospective visitors although it is important to acquire them. Accordingly, we propose a methodology for identifying, acquiring prospective visitors, and recommending the adequate booth information to their preferences in the exhibition industry. We assume that a visitor will be interested in an exhibition within same class of exhibition taxonomy as exhibition which the visitor already saw. Moreover, we use user-based collaborative filtering in order to recommend personalized booths before exhibition. A prototype recommender system is implemented to evaluate the proposed methodology. Our experiments show that the proposed methodology is better than the item-based CF and have an effect on the choice of exhibition or exhibit booth through automation of word-of-mouth communication.