• Journal of Information Management
• /
• v.26 no.2
• /
• pp.1-36
• /
• 1995

The purpose of this study is to analyze fundamental six functions of DIALOG, STN, ORBIT and CDP and then investigate the similarities of the four systems in terms of the functions, and also to compare the commands of these systems with ISO 8777 which is an international standard of command language for the interactive text searching. It was found that there are few differences between the four systems and ISO 8777 in functional aspects, but few similarities in command expression aspects. In addition, it was proven that these four systems are more effective than ISO 8777 in some commands.

• Journal of the Korean Society for information Management
• /
• v.18 no.2
• /
• pp.57-76
• /
• 2001

As the rapid develoment of internet and information technology, the traditional library has been altered to the digital content service based on the world wide web. This paper proposes a design and implementation of an Artcle Union Catalog System(AUCS) based on metadata. The metadata set for the AUCS consists of twelve Dublin Core elements and one holdings element. The qualifiers of the proposed metadata elements are also represented. The AUCS system has an online cooperated cataloging system using the web interface or the 239.50 protocol, an union cataloging management system, and an integrated information retrieved system service. The integrated search and retrieval service of the AUCS displays not only the summary and detailed bibliographic information, but also the abstract, the table of contents, the digital content, and the copylfax service.

• Journal of the Korean Society for information Management
• /
• v.20 no.2
• /
• pp.27-41
• /
• 2003

Query logs are online records that capture user interactions with information retrieval systems and all the search processes. Query log analysis offers ad advantage of providing reasonable and unobtrusive means of collecting search information from a large number of users. In this paper, query logs of NAVER, a major Korean Internet search service, were analyzed to investigate the information seeking behabior of NAVER users. The query logs were collected over one week from various collecions such as comprehensive search, directory search and web ducument searc. It is expected that this study could contribute to the development and implementation of more effective web search systems and services.

• Journal of the Korean Society for Library and Information Science
• /
• v.35 no.3
• /
• pp.17-34
• /
• 2001

It is very important to organize materials at intemet bookstores. It is time for us to develop a subject classification scheme as a tool for increasing the effectiveness of information retrieval with ease of subject access. The purpose of this study is to examine the subject features of internet bookstores in order to suggest the effective design of the subject scheme for them. Nine internet bookstore websites are analyzed at the aspect of the subject classification of the materials. Based upon the results of this study, an effective subject classification for internet bookstores is suggested to provide a better subject access.

• Journal of the Korean Society for information Management
• /
• v.28 no.1
• /
• pp.7-22
• /
• 2011

Internet portals have been revolutionized not only as simple search engines but also as a new space for the Internet users. They have developed to give satisfying search results for academic information users. academic fields. However, their attention was given to the quantity rather than the quality of the results. This tendency is now changing. This study addresses the problems in the search process using the current portal sites and presents an integrated scholarly information service where users can access more organized and trustworthy information linked with online technical keyword dictionary. When a user enter a keyword on a portal site, he/she can access to high quality scholarly information resources linked with keyword. This could assure the user to get an expanded knowledge with confirmation.

• Proceedings of the KAIS Fall Conference
• /
• 2003.11a
• /
• pp.178-184
• /
• 2003

Case-based reasoning (CBR) often shows significant promise for improving effectiveness of complex and unstructured decision making. Consequently, it has been applied to various problem-solving areas including manufacturing, finance and marketing. However, the design of appropriate case indexing and retrieval mechanisms to improve the performance of CBR is still challenging issue. Most of previous studies to improve the effectiveness for CBR have focused on the similarity function or optimization of case features and their weights. However, according to some of prior researches, finding the optimal k parameter for k-nearest neighbor (k-NN) is also crucial to improve the performance of CBR system. Nonetheless, there have been few attempts which have tried to optimize the number of neighbors, especially using artificial intelligence (AI) techniques. In this study, we introduce a genetic algorithm (GA) to optimize the number of neighbors to combine. This study applies the new model to the real-world case provided by an online shopping mall in Korea. Experimental results show that a GA-optimized k-NN approach outperforms other AI techniques for purchasing behavior forecasting.

• Journal of Information Management
• /
• v.33 no.2
• /
• pp.19-32
• /
• 2002

With the growth of the digital library and the use of Internet, the amount of online text information has increased rapidly. The need for efficient data management and retrieval techniques has also become greater. An automatic text categorization system assigns text documents to predefined categories. The system allows to reduce the manual labor for text categorization. In order to classify text documents, the good features from the documents should be selected and the documents are indexed with the features. In this paper, each steps of text categorization and several techniques used in each step are introduced.

• International Journal of Computer Science & Network Security
• /
• v.22 no.5
• /
• pp.182-192
• /
• 2022

All the aspects of human life have been affected by the novel coronavirus (Covid-19). It has rapidly spread in most countries including the Kingdom of Saudi Arabia. As a result, early precautionary actions aiming to minimise the virus effect are taken by the Saudi government. One of these actions is the sudden shift to online classes and suspending the attendees to all educational institutes. Such immediate change can have a significant effect on the educational process, especially for students. One can argue that students' information-seeking behaviour within the current situation can affect their learning quality and outcomes. Therefore, this paper examines the Saudi students' information-seeking behaviour by taking a sample of students from Umm Al-Qura University. A descriptive analysis is conducted with 193 students and two approaches are used to collect data, questionnaire and semi-structured interview. The results showed that the majority of students face difficulties when searching and retrieving e-resources from the university library website. The problems range from mainly poor User Experience (UX), network connection, multiple errors and lack of subscription with academic publishers.

• International Journal of Computer Science & Network Security
• /
• v.23 no.11
• /
• pp.93-98
• /
• 2023

Instagram is one of the fastest-growing online photo social web services where users share their life images and videos with other users. Image tagging is an essential step for developing Automatic Image Annotation (AIA) methods that are based on the learning by example paradigm. Hashtags can be used on just about any social media platform, but they're most popular on Twitter and Instagram. Using hashtags is essentially a way to group together conversations or content around a certain topic, making it easy for people to find content that interests them. Practically on average, 20% of the Instagram hashtags are related to the actual visual content of the image they accompany, i.e., they are descriptive hashtags, while there are many irrelevant hashtags, i.e., stophashtags, that are used across totally different images just for gathering clicks and for search ability enhancement. Hence in this work, Sorting instagram hashtags all the way through mass tagging using HITS (Hyperlink-Induced Topic Search) algorithm is presented. The hashtags can sorted to several groups according to Jensen-Shannon divergence between any two hashtags. This approach provides an effective and consistent way for finding pairs of Instagram images and hashtags, which lead to representative and noise-free training sets for content-based image retrieval. The HITS algorithm is first used to rank the annotators in terms of their effectiveness in the crowd tagging task and then to identify the right hashtags per image.

• The Journal of Information Systems
• /
• v.26 no.3
• /
• pp.171-185
• /
• 2017

Purpose Recently, there has been an increase in attempts to analyze social phenomena, consumption trends, and consumption behavior through a vast amount of customer data such as web search traffic information and social buzz information in various fields such as flu prediction and real estate price prediction. Internet portal service providers such as google and naver are disclosing web search traffic information of online users as services such as google trends and naver trends. Academic and industry are paying attention to research on information search behavior and utilization of online users based on the web search traffic information. Although there are many studies predicting social phenomena, consumption trends, political polls, etc. based on web search traffic information, it is hard to find the research to explain and predict tourism demand and establish tourism policy using it. In this study, we try to use web search traffic information to explain the tourism demand for major cities in Gangwon-do, the representative tourist area in Korea, and to develop a nowcasting model for the demand. Design/methodology/approach In the first step, the literature review on travel demand and web search traffic was conducted in parallel in two directions. In the second stage, we conducted a qualitative research to confirm the information retrieval behavior of the traveler. In the next step, we extracted the representative tourist cities of Gangwon-do and confirmed which keywords were used for the search. In the fourth step, we collected tourist demand data to be used as a dependent variable and collected web search traffic information of each keyword to be used as an independent variable. In the fifth step, we set up a time series benchmark model, and added the web search traffic information to this model to confirm whether the prediction model improved. In the last stage, we analyze the prediction models that are finally selected as optimal and confirm whether the influence of the keywords on the prediction of travel demand. Findings This study has developed a tourism demand forecasting model of Gangwon-do, a representative tourist destination in Korea, by expanding and applying web search traffic information to tourism demand forecasting. We compared the existing time series model with the benchmarking model and confirmed the superiority of the proposed model. In addition, this study also confirms that web search traffic information has a positive correlation with travel demand and precedes it by one or two months, thereby asserting its suitability as a prediction model. Furthermore, by deriving search keywords that have a significant effect on tourism demand forecast for each city, representative characteristics of each region can be selected.