• Proceedings of the Korea Contents Association Conference
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• 2005.05a
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• pp.237-243
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• 2005

As the well-being or quality of life of a population is the common interests, a lot of people are interested in wines. They are willingness to share wine knowledges with other wine experts on the web. Therefore the study for information retrieval system and inference engines are needed to get relevant search results about wine types and suitable wines for given foods. This paper discusses an approach to the architecture of agent-based semantic web services in wine ontology.

• Journal of the Korean Society for Library and Information Science
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• v.31 no.3
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• pp.75-108
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• 1997

The purpose of the article is to help users to select appropriate Korean WWW search tools and to retrieve Web documents for their information needs by using them effectively. It analyzes the characteristics, functions, and advantages and disadvatages of each search tool, while search tools are divided broadly by two categories-subject directory services (Kor-seek, DIR, ZIP, Netquest21, Simmany) and keyword search engines (Simmany, Kachine, Jungbotamjung, Anysearch, Unifinder, Webglider, Missdachanni). It provides the selection criteria of search tools for users who have information needs. In addition, the study also attempts to contribute to the improvements in designing Korean WWW search tools, as investigating their shortcomings.

• Journal of Digital Convergence
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• v.16 no.8
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• pp.169-179
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• 2018

Recently, web search query information has been applied in advanced predictive model research. Google dominates the global web search market in the Korean market; however, Naver possesses a dominant market share. Based on this characteristic, this study intends to compare the utility of the Korean web search query information of Google and Naver using predictive models. Therefore, this study develops three time-series predictive models to estimate the youth unemployment rate in Korea using the ARIMA model. Model 1 only used the youth unemployment rate in Korea, whereas Models 2 and 3 added the Korean web search query information of Naver and Google, respectively, to Model 1. Compared to the predictability of the models during the training period, Models 2 and 3 showed better fit compared with Model 1. Models 2 and 3 correlated different query information. During predictive periods 1 (continuous with the training period) and 2 (discontinuous with the training period), Model 3 showed the best performance. During predictive period 2, only Model 3 exhibited a significant prediction result. This comparative study contributes to a general understanding of the usefulness of Korean web query information using the Naver and Google search engines.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.6
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• pp.1220-1228
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• 2009

Ontologies, which are the core of the Semantic Web, are usually limited by specific domains or created by defining meanings and relationships that depend on the heuristic. However, the creation of an ontology is not only very difficult but also very time-consuming. In contrast with ontologies that are used in specific fields, an ontology for the Web entails an unlimited scope of knowledge and expression of information. Hence, it is hard to express information in the same way that is used to create ontologies in specific fields. Therefore, the automatic generation of an ontology takes very important role in the Semantic Web. In this paper, to make ontologies automatically, we suggest the methods to create and renew ontologies by expanding keywords related to the index-terms which are extracted from the search keywords which users input in the search engines by analyzing the morphemes.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.87-88
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• 2008

As an information service system based on semantic web technology, $OntoFrame^{(R)}$ takes aim at a framework for providing analysis and fusion services of academic information. It currently consists of three parts: ontologies representing knowledge schema derived from academic information, $OntoURI^{(R)}$ which makes academic information into knowledge, and $OntoReasoner^{(R)}$ which performs inference and search on the knowledge. Unlike existing search engines which provides simple search services, our system provides, based on semantic web technology, several semantic and analytic services such as year-based topic trends in academic information, related topics, topic-based researchers and institutes, researcher network, statistics and regional distribution of academic information.

• The Research Journal of the Costume Culture
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• v.13 no.6 s.59
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• pp.934-945
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• 2005

The purpose of this study was to investigate the content and presentation style of consumer information of Korean young casual apparel brand. To collect the data for this study, the representative 25 casual brand web sites were selected, based on major search engines. In addition, to investigate exact product information, four product categories, knit shirts and casual pants for men and women, were selected and the number of products was limited as maximum 15 products per each category. A coding instrument was developed to capture the consumer information, based on the instrument by Park and Stoel(2002). The Pretest was conducted to gauge inter-coder reliability and the results showed that inter-coder reliability was highly acceptable. The results of this study were as follows. Most casual brand web sites for this study were presented well in brand and customer service information. Especially, many web sites provided various engaging information such as various events(best dresser contest, date with a star, special gift) and useful multimedia file(MP3 music file, screen saver, movie, calender). However, product information was very lack in most web sites. Especially, sizing and fitting information and textile and fabric hand information were rarely provided. Therefore, this result showed that the web sites should provide more specific product information and develop devices to get tactile sensory and experiential information for enhancement of future e-commerce of apparel products.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.2
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• pp.65-72
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• 2012

In the 21st century of information systems, the amount of information resources are ever increasing and the role of information searching system is becoming criticalto easily acquire required information from the web. Generally, it requires the user to have enough pre-knowledge and superior capabilities to identify keywords of information to effectively search the web. However, most of the users undertake searching of the information without holding enough pre-knowledge and spend a lot of time associating key words which are related to their required information. Furthermore, many search engines support the keywords searching system but this only provides collection of similar words, and do not provide the user with exact relational search information with the keywords. Therefore this research report proposes a method of offering expanded user relationship search keywords by analyzing user query patterns to provide the user a system, which conveniently support their searching of the information.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.15 no.1
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• pp.23-41
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• 2004

In indexing and organizing Web resources, there have been two basic methods: automatic indexing by extracting key words and library classification schemes or subject directories of search engines. But, both methods have failed to satisfy the user's information needs, due to the lack of standard criteria and the irrationality of its structural system. In this paper I have examined the limits of library classification scheme's structures and the problems related to the nature of Web resources such as specificity and exhaustivity. I have also attempted to explain the logicality of Web resources organization by facet analysis and its strengths and limitations. In so doing, I have proposed three specific methods in using facet analysis: firstly, indexing system by facet analysis; secondly, the alternative transformation of the enumerative classification scheme into facet classification scheme; and finally, the facet model of subject directory of domestic search engine. After examining the three methods, my study concludes that a controlled vocabulary by facet analysis can be employed as a useful method in organizing Web resources.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.189-195
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• 2018

With the advent of the digital age, production and distribution of web pages has been exploding. Internet users frequently need to extract specific information they want from these vast web pages. However, it takes lots of time and effort for users to find a specific information in many web pages. While search engines that are commonly used provide users with web pages containing the information they are looking for on the Internet, additional time and efforts are required to find the specific information among extensive search results. Therefore, it is necessary to develop algorithms that can automatically extract specific information in web pages. Every year, thousands of international conference are held all over the world. Each international conference has a website and provides general information for the conference such as the date of the event, the venue, greeting, the abstract submission deadline for a paper, the date of the registration, etc. It is not easy for researchers to catch the abstract submission deadline quickly because it is displayed in various formats from conference to conference and frequently updated. This study focuses on the issue of extracting abstract submission deadlines from International conference websites. In this study, we use three machine learning models such as SVM, decision trees, and artificial neural network to develop algorithms to extract an abstract submission deadline in an international conference website. Performances of the suggested algorithms are evaluated using 2,200 conference websites.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.2
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• pp.51-73
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• 2015

The Web now provides instant access to an unprecedented amount of information that was unthinkable even 20-30 years ago. However, the full potential of the contents available through the Internet can only be realized when one can speak and understand foreign languages, especially English which accounts for more than half of web contents. In this study, we try to investigate the effect of search task languages and task complexity on searching performance. A total of thirty students enrolled at a top private university in Korea were recruited as study subjects. We set up a quasi-experimental design in which thirty subjects are randomly assigned to a set of eight different search tasks containing an equal number of simple and complex tasks and an equal number of tasks in Korean and in English. The results show that there is a significant difference between simple and complex tasks in terms of SERP time, number of queries used, correctness of results and total search time. However, task language does not seem to have affected search performance for this study group. In addition, students with high English proficiency test scores show comparable search performance in English tasks compared with lower test scores. But we note differences in behavioral patterns (different search engines used and search tactics) among the study participants.