UniWeb 2.0 - 웹을 이용한 클라이언트-서버 데이타베이스 응용 개발 환경

김평철 한국데이터전략학회 1996 Journal of information technology applications & m Vol.3 No.2

웹을 이용한 클라이언트-서버 데이타베이스 시스템은 웹의 서비스 능력과 데이타베이스 시스템의 데이타 관리 기능을 상호 보완적으로 통합함으로써 인터넷과 같은 대규모 환경에서 데이타베이스 업무 환경을 구축하는 데 매우 적합한 것으로 알려져 있다. 데이타베이스 통로는 이러한 통합의 가장 핵심적 구성 요소이다. 본 논문에서는 먼저 클라이언트-서버 데이타베이스 응용을 위한 데이타베이스 통로의 고려사항으로서, 고성능 실행구조, 응용 프로그램 개발 환경, 그리고 상태 및 트랜잭션 관리에 대해 기술하고, 이어서 UniSQL/X용 데이타베이스 통로인 UniWeb 2.0의 설계와 구현에 대하여 소개한다. UniWeb 2.0은 CGI 응용 서버 방식을 채택하여 다양한 플랫폼을 지원하고, 고성능 그리고 확장성을 제공한다. 또한 프로그래머가 HTML 문서에 SQL/X문장이 포함된 Tcl 스크립트를 끼워 넣을 수 있도록 하여 응용 프로그램 개발 생산성을 향상시키고 있다. UniWeb 2.0은 여러 웹 페이지에 걸친 상태 와 트랜잭션을 지원하고 있다.

시공간데이터 분석을 위한 다차원 모델과 시각적 표현에 관한 연구

조재희,서일정,Cho Jae-Hee,Seo Il-Jung 한국데이터전략학회 2006 Journal of information technology applications & m Vol.13 No.1

Spatiotemporal data are records of the spatial changes of moving objects over time. Most data in corporate databases have a spatiotemporal nature, but they are typically treated as merely descriptive semantic data without considering their potential visual (or cartographic) representation. Businesses such as geographical CRM, location-based services, and technologies like GPS and RFID depend on the storage and analysis of spatiotemporal data. Effectively handling the data analysis process may be accomplished through spatiotemporal data warehouse and spatial OLAP. This paper proposes a multidimensional model for spatiotemporal data analysis, and cartographically represents the results of the analysis.

빅데이터 서비스 유형에 따른 개인정보 제공 의도에 관한 연구

정승민 한국데이터전략학회 2022 Journal of information technology applications & m Vol.29 No.3

Recently, big data services have been used in various fields. In this situation, this research studied the intention to provide personal information from users, which is necessary to provide useful big data services. A survey was conducted on college students and ordinary people who have understood big data services. And path analysis was performed through Amos' structural equation. As a result of the study, it was found that privacy risks, trust in service providers, individual innovativeness, service incentives, social influence, and service design are major variables influencing the intention to provide personal information. And it was found that trust in service providers plays a mediating role in influencing the intention to provide personal information. In addition, big data services were classified into types for information acquisition and types related to purchase. Accordingly, it was further analyzed whether major variables differ in the path affecting the intention to provide personal information, and new implications were found. Companies that actually develop and provide big data services should establish different strategies by reflecting research results depending on the type of big data service provided.

하둡과 순차패턴 마이닝 기술을 통한 교통카드 빅데이터 분석

김우생,김용훈,박희성,박진규 한국데이터전략학회 2017 Journal of information technology applications & m Vol.24 No.4

It is urgent to prepare countermeasures for traffic congestion problems of Korea's metropolitan area where central functions such as economic, social, cultural, and education are excessively concentrated. Most users of public transportation in metropolitan areas including Seoul use the traffic cards. If various information is extracted from traffic big data produced by the traffic cards, they can provide basic data for transport policies, land usages, or facility plans. Therefore, in this study, we extract valuable information such as the subway passengers' frequent travel patterns from the big traffic data provided by the Seoul Metropolitan Government Big Data Campus. For this, we use a Hadoop (High-Availability Distributed Object- Oriented Platform) to preprocess the big data and store it into a Mongo database in order to analyze it by a sequential pattern data mining technique. Since we analysis the actual big data, that is, the traffic cards' data provided by the Seoul Metropolitan Government Big Data Campus, the analyzed results can be used as an important referenced data when the Seoul government makes a plan about the metropolitan traffic policies.

데이터베이스 산업 육성정책

이재태 한국데이터전략학회 1994 Journal of information technology applications & m Vol.1 No.2

서로 관련있는 다수의 정보를 체계적으로 수집. 처리하여 컴퓨터등 전자계산조직에 의하여 축적.검색할 수 있도록 한 정보의 집합체가 데이터베이스(DB)이며, 또한 데이터베이스를 제작하는 데이터베이스제작업, 이 데이터베이스를 컴퓨터에 수록하여 이용자에게 제공하는 데이터전송업, 온라인단말기를 설치하고 이용자가 요구하는 정보를 검색.제공하는 정보검색 대행업등으로 구성된 것이 데이터베이스 산업이다.

A Case Study on Data Educational Program for Non-major Trainees

엄혜미 한국데이터전략학회 2023 Journal of information technology applications & m Vol.30 No.5

Due to technological advancements, the data industry is growing, leading to a demand for data professionals in the market. Job seekers interested in data-related positions include not only those with relevant majors but also non-majors. Therefore, this study aims to identify effective educational methods for non-majors lacking data knowledge and skills to develop both data and business competencies. This research focuses on 28 trainees who participated in the “Data Youth Campus” program conducted by K-institution. The program spanned 10 weeks and was structured into three phases: fundamentals, practical training, and projects, systematically enhancing trainees' capabilities. The effectiveness of the curriculum and trainee management was verified by measuring and analyzing improvement of competencies and satisfaction with the program. This study offers valuable insights for the design and implementation of data education programs tailored to non-majors.

Fuel Consumption Prediction and Life Cycle History Management System Using Historical Data of Agricultural Machinery

이정승,김수경 한국데이터전략학회 2022 Journal of information technology applications & m Vol.29 No.5

This study intends to link agricultural machine history data with related organizations or collect them through IoT sensors, receive input from agricultural machine users and managers, and analyze them through AI algorithms. Through this, the goal is to track and manage the history data throughout all stages of production, purchase, operation, and disposal of agricultural machinery. First, LSTM (Long Short-Term Memory) is used to estimate oil consumption and recommend maintenance from historical data of agricultural machines such as tractors and combines, and C-LSTM (Convolution Long Short-Term Memory) is used to diagnose and determine failures. Memory) to build a deep learning algorithm. Second, in order to collect historical data of agricultural machinery, IoT sensors including GPS module, gyro sensor, acceleration sensor, and temperature and humidity sensor are attached to agricultural machinery to automatically collect data. Third, event-type data such as agricultural machine production, purchase, and disposal are automatically collected from related organizations to design an interface that can integrate the entire life cycle history data and collect data through this.

Why Data Capability is Important to become an AI Matured Organization?

김경민 한국데이터전략학회 2024 Journal of information technology applications & m Vol.31 No.3

. Although firms with advanced analytics and machine learning (which is often called AI) capabilities are considered to be highly successful in the market by making decisions and actions based on quantitative analysis using data, the scarcity of historical data and the lack of right data infrastructure are the problems for the organizations to perform such projects. The objective of this study, is to identify a road map for the organization to reach data capability maturity to become AI matured organizations. First, this study defines the terms, AI capability, data capability and AI matured organization. Then using content analyses, organizations’ data practices performed for AI system development and operation are analyzed to infer a data capability roadmap to become an AI matured organization.

반사실적 데이터 증강에 기반한 인과추천모델: CausRec사례

송희석 한국데이터전략학회 2023 Journal of information technology applications & m Vol.30 No.4

A single-learner model which integrates the user's positive and negative perceptions is proposed by augmenting counterfactual data to the interaction data between users and items, which are mainly used in collaborative filtering in this study. The proposed CausRec showed superior performance compared to the existing NCF model in terms of F1 value and AUC in experiments using three published datasets: MovieLens 100K, Amazon Gift Card, and Amazon Magazine. Compared to the existing NCF model, the F1 and AUC values of CausRec showed 1.2% and 2.6% performance improvement in MovieLens 100K data, and 2.2% and 10% improvement in Amazon Gift Card data, respectively. In particular, in experiments using Amazon Magazine data, F1 and AUC values were improved by 11.7% and 21.9%, respectively, showing a significant performance improvement effect. The performance of CausRec is improved because both positive and negative perceptions of the item were reflected in the recommendation at the same time. It is judged that the proposed method was able to improve the performance of the collaborative filtering because it can simultaneously alleviate the sparsity and imbalance problems of the interaction data.

Requirement-Oriented Entity Relationship Modeling

이상원,신경식 한국데이터전략학회 2010 Journal of information technology applications & m Vol.17 No.3

Most of enterprises depend on a data modeler during developing their management information systems. In formulating business requirements for information systems, they widely and naturally use the interview method between a data modeler and a field worker. But, the discrepancy between both parties would certainly cause information loss and distortion that lead to let the systems not faithful to real business works. To improve or avoid modeler-dependant data modeling process, many automated data design CASE tools have been introduced. However, since most of traditional CASE tools just support drawing works for conceptual data design, a data modeler could not generate an ERD faithful to real business works and a user could not use them without any knowledge on database. Although some CASE tools supported conceptual data design, they still required too much preliminary database knowledge for a user. Against these traditional CASE tools, we proposed a Requirement- Oriented Entity Relationship Model for automated data design tool, called ROERM. Based on Non-Stop Methodology, ROERM adopts inner systematic modules for complete and sound ERD that is faithful to real field works, where modules are composed of interaction modules with a user, rules of schema operations and sentence translations. In addition to structure design of ROERM, we also devise detailed algorithms and perform an experiment for a case study.