• 지식경영연구
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• 제19권1호
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• pp.119-132
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• 2018

Many advanced products and services are emerging in the market thanks to data-based technologies such as Internet (IoT), Big Data, and AI. The construction of a system for data processing under the IoT network environment is not simple in configuration, and has a lot of restrictions due to a high cost for constructing a high performance server environment. Therefore, in this paper, we will design a development environment for large data analysis computing platform using open source with low cost and practicality. Therefore, this study intends to implement a big data processing system using Raspberry Pi, an ultra-small PC environment, and open source API. This big data processing system includes building a portable server system, building a web server for web mining, developing Python IDE classes for crawling, and developing R Libraries for NLP and visualization. Through this research, we will develop a web environment that can control real-time data collection and analysis of web media in a mobile environment and present it as a curriculum for non-IT specialists.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2002년도 추계학술대회 및 정기총회
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• pp.443-446
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• 2002

In this research, we suggest a Web-based hybrid recommendation mechanism using CBR (Case-Based Reasoning) and web data mining. Data mining is used as an efficient mechanism in reasoning for relationship between goods, customers' preference and future behavior. CBR systems are normally used in problems for which it is difficult to define rules. We use CBR as an AI tool to recommend the similar purchase case. A Web-log data gathered in real-world Internet shopping mall was given to illustrate the quality of the proposed mechanism. The results showed that the CBR and web data mining-based hybrid recommendation mechanism could reflect both association knowledge and purchase information about our former customers.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제7권2호
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• pp.91-95
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• 2007

Main goal of web recommendation system is to study how user behavior on a website can be predicted by analyzing web log data which contain the visited web pages. Many researches of the web recommendation system have been studied. To construct web recommendation system, web mining is needed. Especially, web usage analysis of web mining is a tool for recommendation model. In this paper, we propose web recommendation system using grid based support vector machines for improvement of web recommendation system. To verify the performance of our system, we make experiments using the data set from our web server.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2013년도 추계학술대회
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• pp.836-838
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• 2013

최근 정보 기술의 발전 방향은 소셜 컴퓨팅(social computing), 모바일 컴퓨팅(mobile computing), 클라우드 컴퓨팅(cloud computing)으로 대표되고 있다. 최근 웹 기술은 IT 분야를 넘어 산업 간 융합을 위한 서비스 측면의 매개기술로 발전하고 있으며, 특히 웹 기반 데이터의 급속한 증가로 개방형 웹 데이터는 차세대 웹 기술의 중요성이 높아지고 있다. 이에 본 논문에서는 차세대 웹 기술의 중요성이 높아지고 있는 개방형 웹 데이터의 국내외 표준화 동향에 대해 연구하였다.

• Journal of Information Science Theory and Practice
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• 제2권4호
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• pp.61-76
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• 2014

The exponential growth of information on the web far exceeds the capacity of present day information retrieval systems and search engines, making information integration on the web difficult. In order to overcome this, semantic web technologies were proposed by the World Wide Web Consortium (W3C) to achieve a higher degree of automation and precision in information retrieval systems. Semantic web, with its promise to deliver machine understanding to the traditional web, has attracted a significant amount of research from academia as well as from industries. Semantic web is an extension of the current web in which data can be shared and reused across the internet. RDF and ontology are two essential components of the semantic web architecture which support a common framework for data storage and representation of data semantics, respectively. Ontologies being the backbone of semantic web applications, it is more relevant to study various approaches in their application, usage, and integration into web services. In this article, an effort has been made to review the research work being undertaken in the area of design and development of ontology supported information systems. This paper also briefly explains the emerging semantic web technologies and standards.

• 한국항행학회논문지
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• 제22권5호
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• pp.467-471
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• 2018

4차 산업혁명을 거치면서 사용자들이 활용할 수 있는 데이터의 양이 급증했다. 그리고 이는 웹 기술을 활용한 ECMA script, WebAssembly, web of things 등 다양한 융합 기술들이 등장하는 발판이 되었다. 웹을 통해 공유되는 데이터의 양이 증가함에 따라 웹은 현대인의 삶에서 가장 영향력 있는 매체로 부상했다. 따라서 웹 개발자들은 웹을 통해 데이터를 빠르게 전달하기 위해 노력했다. 그래서 다양한 웹 애플리케이션 분석 도구들이 등장하였고, 웹 애플리케이션의 문제 분석을 통해 속도 문제의 해결책을 찾고자했다. 하지만 웹 애플리케이션 성능 분석을 위한 도구의 성능은 크게 발전하지 못하였다. 대부분의 현존 분석 툴들은 직접적인 설치를 요구하며, 분석을 진행하기 위해서는 웹에 대한 전문 지식을 요구하고, WebAssembly와 같은 웹 신기술을 반영하지 못하고 있다. 따라서 본 논문에서는 기존 웹 애플리케이션 분석 툴의 문제점을 개선할 수 있는 새로운 리포팅 솔루션의 설계를 제안하고자 한다.

• 한국정보전자통신기술학회논문지
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• 제12권6호
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• pp.681-689
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• 2019

웹 사용 패턴 발견은 웹 로그 데이터를 사용하는 고급 수단이며 웹 로그 데이터 마이닝에 데이터 마이닝 기술을 적용한 특정 응용이다. 교육 분야에서 데이터 마이닝 (DM)은 데이터 마이닝 기술을 교육 데이터 (대학의 웹 로그, e-러닝, 적응형 하이퍼미디어 및 지능형 튜터링시스템 등)에 적용한다. 따라서 교육 연구 문제를 해결하기 위해 이러한 유형의 데이터를 분석하는 것이 목표이다. 본 논문에서는 대학의 웹 로그 데이터가 데이터 마이닝의 연구 대상으로 사용되어 진다. 데이터베이스 OLAP 기술을 사용하여 웹 로그 데이터가 데이터 마이닝에 사용될 수 있는 데이터 형식으로 사전 처리되고 그 처리 결과가 MSSQL에 저장된다. 동시에 처리 된 웹 로그 레코드를 기반으로 기본 데이터 통계 및 분석이 완료된다. 또한 웹 사용 패턴 마이닝의 Apriori Algorithm 및 구현 프로세스를 소개하고 Python 개발 환경에서 Apriori Algorithm 프로그램을 개발했다. 그런 다음 Apriori Algorithm의 성능을 보이고 웹 사용자 액세스 패턴의 마이닝을 실현했다. 이 연구 결과는 교육 시스템 개발에 패턴을 적용하는데 중요한 이론적 의미를 갖는다. 다음 연구로는 분산 컴퓨팅 환경에서 Apriori Algorithm의 성능 향상을 연구하는 것이다.

• International Journal of Contents
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• 제1권2호
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• pp.5-9
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• 2005

Currently most Internet documents including data are made based on predefined templates, but templates are usually formed only for main data and are not helpful for information retrieval against indexes, advertisements, header data etc. Templates in such forms are not appropriate when Internet documents are used as data for information retrieval. In order to process Internet documents in various areas of information retrieval, it is necessary to detect additional information such as advertisements and page indexes. Thus this study proposes a method of detecting the layout of Web pages by identifying the characteristics and structure of block tags that affect the layout of Web pages and calculating distances between Web pages. This method is purposed to reduce the cost of Web document automatic processing and improve processing efficiency by providing information about the structure of Web pages using templates through applying the method to information retrieval such as data extraction.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2006년도 추계학술대회 학술발표 논문집 제16권 제2호
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• pp.408-411
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• 2006

Currently, the nano economy threatens the mass economy. This is based on the internet business models. In the nano business models based on internet, the diversely personalized services are needed. Many researches of the personalization on the web have been studied. The web usage mining using click stream data is a tool for personalization model. In this paper, we propose an internet business model using evolutionary support vector machine and web response survey as a web usage mining. After analyzing click stream data for web usage mining, a personalized service model is constructed in our work. Also, using an approach of web response survey, we improve the performance of the customers' satisfaction. From the experimental results, we verify the performance of proposed model using two data sets from KDD Cup 2000 and our web server.

• 한국경영과학회지
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• 제33권3호
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• pp.29-42
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• 2008

Semantic Web society initially focused only on data but has gradually moved toward knowledge. Recently rule beyond ontology has emerged as a key element of the Semantic Web. All of these activities are obviously aiming at making data and knowledge on the Web sharable and reusable between various entities around the world. If one of ultimate visions of the Semantic Web is to increase human's decision making quality assisted by machines, there is a missing but important part to be shared and reused. It is knowledge about constraints on data and concepts represented by ontology which should be emphasized more. In this paper, we propose Semantic Web Constraint Language (SWCL) based on OWL and show how effective SWCL can be in representing and solving an internet shopper's decision making problem by an implementation of a shopping agent in the Semantic Web environment.