• Title/Summary/Keyword: 지능형 기업정보지원 시스템

Search Result 33, Processing Time 0.018 seconds

An Ontology Model for Public Service Export Platform (공공 서비스 수출 플랫폼을 위한 온톨로지 모형)

  • Lee, Gang-Won;Park, Sei-Kwon;Ryu, Seung-Wan;Shin, Dong-Cheon
    • Journal of Intelligence and Information Systems
    • /
    • v.20 no.1
    • /
    • pp.149-161
    • /
    • 2014
  • The export of domestic public services to overseas markets contains many potential obstacles, stemming from different export procedures, the target services, and socio-economic environments. In order to alleviate these problems, the business incubation platform as an open business ecosystem can be a powerful instrument to support the decisions taken by participants and stakeholders. In this paper, we propose an ontology model and its implementation processes for the business incubation platform with an open and pervasive architecture to support public service exports. For the conceptual model of platform ontology, export case studies are used for requirements analysis. The conceptual model shows the basic structure, with vocabulary and its meaning, the relationship between ontologies, and key attributes. For the implementation and test of the ontology model, the logical structure is edited using Prot$\acute{e}$g$\acute{e}$ editor. The core engine of the business incubation platform is the simulator module, where the various contexts of export businesses should be captured, defined, and shared with other modules through ontologies. It is well-known that an ontology, with which concepts and their relationships are represented using a shared vocabulary, is an efficient and effective tool for organizing meta-information to develop structural frameworks in a particular domain. The proposed model consists of five ontologies derived from a requirements survey of major stakeholders and their operational scenarios: service, requirements, environment, enterprise, and county. The service ontology contains several components that can find and categorize public services through a case analysis of the public service export. Key attributes of the service ontology are composed of categories including objective, requirements, activity, and service. The objective category, which has sub-attributes including operational body (organization) and user, acts as a reference to search and classify public services. The requirements category relates to the functional needs at a particular phase of system (service) design or operation. Sub-attributes of requirements are user, application, platform, architecture, and social overhead. The activity category represents business processes during the operation and maintenance phase. The activity category also has sub-attributes including facility, software, and project unit. The service category, with sub-attributes such as target, time, and place, acts as a reference to sort and classify the public services. The requirements ontology is derived from the basic and common components of public services and target countries. The key attributes of the requirements ontology are business, technology, and constraints. Business requirements represent the needs of processes and activities for public service export; technology represents the technological requirements for the operation of public services; and constraints represent the business law, regulations, or cultural characteristics of the target country. The environment ontology is derived from case studies of target countries for public service operation. Key attributes of the environment ontology are user, requirements, and activity. A user includes stakeholders in public services, from citizens to operators and managers; the requirements attribute represents the managerial and physical needs during operation; the activity attribute represents business processes in detail. The enterprise ontology is introduced from a previous study, and its attributes are activity, organization, strategy, marketing, and time. The country ontology is derived from the demographic and geopolitical analysis of the target country, and its key attributes are economy, social infrastructure, law, regulation, customs, population, location, and development strategies. The priority list for target services for a certain country and/or the priority list for target countries for a certain public services are generated by a matching algorithm. These lists are used as input seeds to simulate the consortium partners, and government's policies and programs. In the simulation, the environmental differences between Korea and the target country can be customized through a gap analysis and work-flow optimization process. When the process gap between Korea and the target country is too large for a single corporation to cover, a consortium is considered an alternative choice, and various alternatives are derived from the capability index of enterprises. For financial packages, a mix of various foreign aid funds can be simulated during this stage. It is expected that the proposed ontology model and the business incubation platform can be used by various participants in the public service export market. It could be especially beneficial to small and medium businesses that have relatively fewer resources and experience with public service export. We also expect that the open and pervasive service architecture in a digital business ecosystem will help stakeholders find new opportunities through information sharing and collaboration on business processes.

Security Credential Management & Pilot Policy of U.S. Government in Intelligent Transport Environment (지능형 교통 환경에서 미국정부의 보안인증관리 & Pilot 정책)

  • Hong, Jin-Keun
    • Journal of Convergence for Information Technology
    • /
    • v.9 no.9
    • /
    • pp.13-19
    • /
    • 2019
  • This paper analyzed the SCMS and pilot policy, which is pursued by the U.S. government in connected vehicles. SCMS ensures authentication, integrity, privacy and interoperability. The SCMS Support Committee of U.S. government has established the National Unit SCMS and is responsible for system-wide control. Of course, it introduces security policy, procedures and training programs making. In this paper, the need for SCMS to be applied to C-ITS was discussed. The structure of the SCMS was analyzed and the U.S. government's filot policy for connected vehicles was discussed. The discussion of the need for SCMS highlighted the importance of the role and responsibilities of SCMS between vehicles and vehicles. The security certificate management system looked at the structure and analyzed the type of certificate used in the vehicle or road side unit (RSU). The functions and characteristics of the certificates were reviewed. In addition, the functions of basic safety messages were analyzed with consideration of the detection and warning functions of abnormal behavior in SCMS. Finally, the status of the pilot project for connected vehicles currently being pursued by the U.S. government was analyzed. In addition to the environment used for the test, the relevant messages were also discussed. We also looked at some of the issues that arise in the course of the pilot project.

A Study on Enhancing Personalization Recommendation Service Performance with CNN-based Review Helpfulness Score Prediction (CNN 기반 리뷰 유용성 점수 예측을 통한 개인화 추천 서비스 성능 향상에 관한 연구)

  • Li, Qinglong;Lee, Byunghyun;Li, Xinzhe;Kim, Jae Kyeong
    • Journal of Intelligence and Information Systems
    • /
    • v.27 no.3
    • /
    • pp.29-56
    • /
    • 2021
  • Recently, various types of products have been launched with the rapid growth of the e-commerce market. As a result, many users face information overload problems, which is time-consuming in the purchasing decision-making process. Therefore, the importance of a personalized recommendation service that can provide customized products and services to users is emerging. For example, global companies such as Netflix, Amazon, and Google have introduced personalized recommendation services to support users' purchasing decisions. Accordingly, the user's information search cost can reduce which can positively affect the company's sales increase. The existing personalized recommendation service research applied Collaborative Filtering (CF) technique predicts user preference mainly use quantified information. However, the recommendation performance may have decreased if only use quantitative information. To improve the problems of such existing studies, many studies using reviews to enhance recommendation performance. However, reviews contain factors that hinder purchasing decisions, such as advertising content, false comments, meaningless or irrelevant content. When providing recommendation service uses a review that includes these factors can lead to decrease recommendation performance. Therefore, we proposed a novel recommendation methodology through CNN-based review usefulness score prediction to improve these problems. The results show that the proposed methodology has better prediction performance than the recommendation method considering all existing preference ratings. In addition, the results suggest that can enhance the performance of traditional CF when the information on review usefulness reflects in the personalized recommendation service.