• Journal of Internet Computing and Services
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• v.10 no.5
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• pp.95-105
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• 2009

There are various studies to provide useful information for users on huge data of web-sites. Web usage mining among them is a method to extract meaningful patterns based on web users' log data. Most of existing patterns of web usage mining, however, had not considered users' diverse inclination but created general models. Web users' keywords can have various meaning upon their tendency and background knowledge. This study is for generating Multi Concept Keyword Model (MCK-Model) by analyzing web usage information on users' keywords of interest. MCK-Model can supply web page network for various inclination based on users' keywords of interest. Also, MCK-Model can be used to recommend the most proper web pages and it has been confirmed that the suggested method is useful enough.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.7-12
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• 2004

본 연구에서는 효율적인 전자상거래를 위해 Web Mining을 기반으로 고객의 수요를 예측하고 고객요구에 대응한 능동적인 생산을 위해 생산자의 구매수요를 공급자의 입장에서 예측하는 방법을 제안하였다. 먼저, 고객의 구매정보를 분석하여 다양한 고객의 구매패턴을 찾아내고 이를 통해 고객의 수요를 예측하였다. 이렇게 예측된 수요는 생산업체에 모여져 생산전략을 수립하게 된다. 생산전략이 수립되면 생산업체는 부품의 수급을 위해 공급업체에 대한 부품 구매일정과 고객의 장기 구매패턴을 고려한 생산일정을 수립하게 된다. 이렇게 수립된 구매일정과 생산일정에 의해 공급자에 대한 주문과 생산이 이루어지는데 이때 공급자의 입장에서 구매자의 요구에 능동적으로 대응하기 위해서는 구매자에 대한 이해가 필요하며 이를 이해 공급자가 자신이 공급하는 구매업체들의 거래정보를 분석하게 된다. 본 연구에는 이와 같이 고객과 생산업체, 구매업체와 공급업체를 하나로 연결하여 분석하였다.

• Journal of the Korean Home Economics Association
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• v.43 no.3 s.205
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• pp.1-10
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• 2005

The purpose of this study was to investigate the enforcement strategy for Consumer Service marketing of an e-Commerce shopping mall. An e-CRM for a Cosmetic e-Commerce shopping mall, Data Warehousing(DW) component, analysis of data mining of the DW, and web applications and strategies had to developed for marketing of consumer service satisfaction. The major findings were as follows: An RFM analysis was used for consumer classification, which is a fundamental process of e-CRM application. The components of the DW were web sales data and consumer data fields. The visual process of consumer segmentations (superior consumer class) for e-CRM solutions is presented. The association analysis algorithm of data mining to up-selling and cross-selling indicates an association rule. These e-CRM results apply web DB marketing and operating principles to a shopping mall. Therefore, the system applications of e-CRM to Consumer services indicate a marketing strategy for consumer-oriented management.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.4
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• pp.703-708
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• 2020

The momentum of e-commerce is growing stronger and now, the competition between e-commerce is becoming more and more fierce. In the competition of various e-commerce companies, how to effectively analyze and rationally use these data has become a key point. This paper will use data mining technology to filter out redundant data from large Web databases, extract data that is useful to us, and then analyze them from different perspectives to apply this data reasonably and effectively to our e-commerce website.

• Journal of KIISE:Software and Applications
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• v.31 no.1
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• pp.61-70
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• 2004

It is difficult to find an appropriate web site because exponentially growing web contains millions of web documents. Personalization of web search can be realized by recommending proper web sites using user profile but more efficient method is needed for estimating preference because user's evaluation on web contents presents many aspects of his characteristics. As user profile has a property of non-linearity, estimation by classifier is needed and combination of classifiers is necessary to anticipate diverse properties. Structure adaptive self-organizing map (SASOM) that is suitable for Pattern classification and visualization is an enhanced model of SOM and might be useful for web mining. Fuzzy integral is a combination method using classifiers' relevance that is defined subjectively. In this paper, estimation of user profile is conducted by using ensemble of SASOM's teamed independently based on fuzzy integral and evaluated by Syskill ＆ Webert UCI benchmark data. Experimental results show that the proposed method performs better than previous naive Bayes classifier as well as voting of SASOM's.

• KIISE Transactions on Computing Practices
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• v.22 no.2
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• pp.83-88
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• 2016

Subtopic mining is the extraction and ranking of possible subtopics, which disambiguate and specify the search intentions of an input query in terms of relevance, popularity, and diversity. This paper describes the limitations of previous studies on the utilization of web resources, and proposes a subtopic mining method with a two-level hierarchy based on hierarchical search intentions and web resources, in order to overcome these limitations. Considering the characteristics of resources provided by the official subtopic mining task, we extract various second-level subtopics reflecting hierarchical search intentions from web documents, and expand and re-rank them using other provided resources. Terms in subtopics with wider search intentions are used to generate first-level subtopics. Our method performed better than state-of-the-art methods in almost every aspect.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4467-4488
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• 2014

The bibliometric analysis is widely used for understanding research domains, trends, and knowledge structures in a particular field. The analysis has majorly been used in the field of information science, and it is currently applied to other academic fields. This paper describes the analysis of academic literatures for classifying research domains and for suggesting empty research areas in the telecommunications policy. The application software is developed for retrieving Thomson Reuters' Web of Knowledge (WoK) data via web services. It also used for conducting text mining analysis from contents and citations of publications. We used three text mining techniques: the Keyword Extraction Algorithm (KEA) analysis, the co-occurrence analysis, and the citation analysis. Also, R software is used for visualizing the term frequencies and the co-occurrence network among publications. We found that policies related to social communication services, the distribution of telecommunications infrastructures, and more practical and data-driven analysis researches are conducted in a recent decade. The citation analysis results presented that the publications are generally received citations, but most of them did not receive high citations in the telecommunications policy. However, although recent publications did not receive high citations, the productivity of papers in terms of citations was increased in recent ten years compared to the researches before 2004. Also, the distribution methods of infrastructures, and the inequity and gap appeared as topics in important references. We proposed the necessity of new research domains since the analysis results implies that the decrease of political approaches for technical problems is an issue in past researches. Also, insufficient researches on policies for new technologies exist in the field of telecommunications. This research is significant in regard to the first bibliometric analysis with abstracts and citation data in telecommunications as well as the development of software which has functions of web services and text mining techniques. Further research will be conducted with Big Data techniques and more text mining techniques.

• The KIPS Transactions:PartD
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• v.13D no.3 s.106
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• pp.299-308
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• 2006

As recently XML is becoming the standard of exchanging web documents and public documentations, XML data are increasing in many areas. To retrieve the information about XML documents efficiently, the semantic web based on the ontology is appearing. The existing ontology has been constructed manually and it was time and cost consuming. Therefore in this paper, we propose the semi-automatic ontology generation technique using the data mining technique, the association rules. The proposed method solves what type and how many conceptual relationships and determines the ontology domain level for the automatic ontology generation, using the data mining algorithm. Appying the association rules to the XML documents, we intend to find out the conceptual relationships to construct the ontology, finding the frequent patterns of XML tags in the XML documents. Using the conceptual ontology domain level extracted from the data mining, we implemented the semantic web based on the ontology by XML Topic Maps (XTM) and the topic map engine, TM4J.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.46-48
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• 2001

현재 수많은 웹사이트들이 웹상에 존재하며 서비스를 하고 있다. 사용자는 여러 웹사이트 중에서 접속하기 편하고 잘 구성된 웹사이트에 접속하기 마련이므로, 잘 구성된 웹사이트 운영은 그 웹사이트의 생존 전략이며 방문자 유지에 필수적이다. 이를 위해 사용자들이 웹사이트에 접속한 기록이 남아 있는 웹서버 로그데이터(이하 웹 로그파일)를 분석하여 사용자들의 브라우징 패턴과 접속 경향, 웹 서버의 에러발생 정보 등을 파악할 수 있다. 본 논문에서는 Web Usage Mining 과 Web Structure Mining 작업으로 로그파일 분석과 웹사이트 구조분석을 수행하여 페이지들의 연관 관계와 웹사이트의 구조 정보를 발견해서 웹사이트의 구조를 개선하는 방안을 제안하고자 한다.

• The Journal of Information Technology
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• v.12 no.3
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• pp.7-17
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• 2009

This research is about the design of an opinion drawing and analysis system through statistical based Web Mining of web contents, where data of opinions are automatically drawn and analyzed concerning web documents that are scattered around in various web sites that exist within the internet. Furthermore, provides a search service that can easily classify positive/negative opinions and also provide searching and statistical information. Users, who want to search for opinions, can input a specific keyword to observe opinions of others easily. In addition, there is a merit in materializing the monitoring system.