• Proceedings of the Korea Contents Association Conference
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• 2004.11a
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• pp.269-274
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• 2004

Because of the rapid development of internet and Various Types. huge amount and Various types of data are available on the web there days. The tasks such as information retrieval, composition and integration are not easy on the web which contains such huge amount of data. In order to solve these problems W3C introduced Semantic Web as a next generation Web. Semantic Web guarantee the cooperation between heterogeneous Systems and improve reusability of information by providing the machine understandable Web data. In this paper. We design develop an ontology for the museum. The implemented ontology can be used as a standard ontology for the relic search in a museum.

• Journal of KIISE:Software and Applications
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• v.31 no.8
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• pp.1101-1112
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• 2004

In this paper, we propose a Web page weighting scheme using the user preference in each sense of query word to improve the performance of Web search. Generally search engines assign weights to a web page by using relevancy only, which is obtained by comparing the query word and the words in a web page. In the information retrieval from huge data such as the Web, simple word comparison cannot distinguish important documents because there exist too many documents with similar relevancy In this paper we implement a WordNet-based user interface that helps to distinguish different senses of query word, and constructed a search engine in which the implicit evaluations by multiple users are reflected in ranking by accumulating the number of clicks. In accumulating click counts, they are stored separately according to senses, so that more accurate search is possible. The experimental results with several keywords show that the precision of proposed system is improved compared to conventional search engines.

• Journal of the Korean Society for Library and Information Science
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• v.51 no.2
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• pp.255-279
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• 2017

In a qualitative approach, this study investigated users' perceptions associated with their satisfactions in the process of using the scholarly resource search functions of the academic version of the NAVER search engine. For this study, the data was collected from a group of undergraduate students, who conducted academic information searches in the field of own major disciplinary areas, using the Web portal. Based on the data, students' satisfactions and dissatisfactions along with the reasons of their perceptions were analyzed. The results presented users' perceptions in various evaluation criteria based on the three major domains: system interfaces, retrieval mechanisms and search results. Based on the results, the study proposed the following suggestions: 1) the enhancements of the system interfaces and HELP guidances based the limited user knowledge on basic system terminologies 2) the improvements of the retrieval mechanisms associated with understanding the contexts of the search terms presented by users 3) the necessity of the user education due to the insufficient user knowledge of the retrieval mechanisms and the search functions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.623-625
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• 2003

The Semantic Web stands out in the next generation web, recently. In the Semantic Web, any information resources is defined by semantics and semantic links is given among these. It is different from existing web service environment. RDF (Resource Description Framework) is the data model to describe metadata of web resource and is to support for semantic links. And it is much the same as WSDL (Web Serice Description Language). In theis paper, we propose the RDF design method to improve the search performance by integrating RDF data unit with WSDL. We confirm the performance and efficiency of search will be improved by using the proposed method.

• The Journal of the Korea Contents Association
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• v.13 no.12
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• pp.575-584
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• 2013

Data types used for big-data analysis are very widely, such as news, blog, SNS, papers, patents, sensed data, and etc. Particularly, the utilization of web documents offering reliable data in real time is increasing gradually. And web crawlers that collect web documents automatically have grown in importance because big-data is being used in many different fields and web data are growing exponentially every year. However, existing web crawlers can't collect whole web documents in a web site because existing web crawlers collect web documents with only URLs included in web documents collected in some web sites. Also, existing web crawlers can collect web documents collected by other web crawlers already because information about web documents collected in each web crawler isn't efficiently managed between web crawlers. Therefore, this paper proposed a distributed web crawler. To resolve the problems of existing web crawler, the proposed web crawler collects web documents by RSS of each web site and Google search API. And the web crawler provides fast crawling performance by a client-server model based on RMI and NIO that minimize network traffic. Furthermore, the web crawler extracts core content from a web document by a keyword similarity comparison on tags included in a web documents. Finally, to verify the superiority of our web crawler, we compare our web crawler with existing web crawlers in various experiments.

• The Journal of the Korea Contents Association
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• v.5 no.6
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• pp.1-9
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• 2005

As the amount of data on the web increase, it is difficult to search what we want exactly. Therefore, much researches are attempted to search web resources efficiently. So, W3C established the standard that give meanings to resources on the web using RDF metadata. The RDF metadata had been mainly described a document data on the web. But it is difficult to create automatically the metadata for application programs than the document data. This paper proposes a method to use RDF metadata to search application programs. Firstly, we define RDF data model that stores the information of the application programs and RDF schema that references the RDF data model. And we design a prototype system to search application programs. This system meets expectation, getting the application to fullfill the needs of user, and has the efficiency of the searching function.

• Fashion & Textile Research Journal
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• v.17 no.5
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• pp.731-740
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• 2015

Mobile (smartphone) search engine marketing is increasingly important. Accordingly, the development of visual apparel search technology to obtain easier and faster access to visual information in the apparel field is urgently needed. This study helps establish a proper classifying system for an apparel search after an analysis of search techniques for apparel search applications and existing domestic and overseas apparel sites. An annotation technique is developed in accordance with visual attributes and apparel categories based on collected data obtained by web crawling and apparel images collecting. The categorical composition of apparel is divided into wearing, image and style. The web evaluation site traces the correlations of the apparel category and apparel factors as dependent upon visual attributes. An appraisal team of 10 individuals evaluated 2860 pieces of merchandise images. Data analysis consisted of correlations between apparel, sleeve length and apparel category (based on an average analysis), and correlation between fastener and apparel category (based on an average analysis). The study results can be considered as an epoch-making mobile apparel search system that can contribute to enhancing consumer convenience since it enables an effective search of type, price, distributor, and apparel image by a mobile photographing of the wearing state.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.11a
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• pp.287-296
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• 2002

웹 사용 마이닝은 데이터마이닝을 바탕으로 사용자의 로그 파일 정보를 이용하여 웹이 이용되는 패턴을 발견한다. 이를 이용하여 웹을 개선하여 사용자들이 보다 빨리 원하는 내용을 검색할 수 있도록 할 수 있으며 시스템 관리자에게는 효율적인 웹 구조를 인한 정보를 제공할 수 있다. 웹 사용 마이닝에서 사용하는 데이터는 성형화되어 있지 않으며 웹 사용 패턴을 분석하는데 방해가 되는 잡음 데이터까지 포함하고 있다. 이것은 기존에 개발된 여러 데이터마이닝 기법을 적용하는데 어려움으로 작용한다. 이러한 어려움을 해결하기 위해 본 논문에서는 새로운 방법을 도입한 SPMiner을 .제안한다. SPMiner는 웹의 구조를 이용하여 로그 파일의 전처리 과정을 줄이며 사용자의 탐색 패턴 분석을 효율적으로 수행 할 수 있는 시스템이다. SPMiner는 WebTree 에이전트를 이용하여 웹 사이트 구조를 분석하여 WebTree를 생성하고 사용자 로그 파일을 분석하여 각 웹 페이지의 사용빈도에 대한 정보를 추출한다. WebTree와 로그 파일에서 추출된 웹 페이지에 대한 정보는 SPMiner에 의해 패턴을 분석할 퍼 이용될 수 있는 형태인 WebTree$^{+}$로 병합된다 WebTree$^{+}$는 패턴 발견을 쉽게 해주며 사용자에게 추천할 정보나 웹 페이지를 능동적으로 추천할 수 있게 만들어 준다.

• Journal of Information Processing Systems
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• v.9 no.2
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• pp.217-236
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• 2013

Ranking thousands of web documents so that they are matched in response to a user query is really a challenging task. For this purpose, search engines use different ranking mechanisms on apparently related resultant web documents to decide the order in which documents should be displayed. Existing ranking mechanisms decide on the order of a web page based on the amount and popularity of the links pointed to and emerging from it. Sometime search engines result in placing less relevant documents in the top positions in response to a user query. There is a strong need to improve the ranking strategy. In this paper, a novel ranking mechanism is being proposed to rank the web documents that consider both the HTML structure of a page and the contextual senses of keywords that are present within it and its back-links. The approach has been tested on data sets of URLs and on their back-links in relation to different topics. The experimental result shows that the overall search results, in response to user queries, are improved. The ordering of the links that have been obtained is compared with the ordering that has been done by using the page rank score. The results obtained thereafter shows that the proposed mechanism contextually puts more related web pages in the top order, as compared to the page rank score.

• Journal of the Korean Society for information Management
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• v.24 no.2
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• pp.29-44
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• 2007

The purpose of this study was to explore whether the concept of amount of invested mental effort (AIME) developed in the field of educational psychology can help explain why people put so little effort into online searching. In this experimental study, two information retrieval systems - a web search engine and a university library system - were used to make a comparison. The data were collected from 15 undergraduate students through background questionnaires, think-aloud protocols, search logs, post-search questionnaires, and post-task interviews. The findings indicate that perception of the web's "easy-ness" and high levels of self confidence in searching capability led the subjects to put less effort into web searching than they do into library system searching. In addition, the perceived difficulty of search task influenced the extent of mental effort invested. The AIME proved a useful framework for understanding search behavior and user experience for both web search engines and library systems.