• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1868-1887
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• 2024

Recommendation systems research is a subfield of information retrieval, as these systems recommend appropriate items to users during their visits. Appropriate recommendation results will help users save time searching while increasing productivity at work, travel, or shopping. The problem becomes more difficult when the items are geographical locations on the ground, as they are associated with a wealth of contextual information, such as geographical location, opening time, and sequence of related locations. Furthermore, on social networking platforms that allow users to check in or express interest when visiting a specific location, their friends receive this signal by spreading the word on that online social network. Consideration should be given to relationship data extracted from online social networking platforms, as well as their impact on the geolocation recommendation process. In this study, we compare the similarity of geographic locations based on their distance on the ground and their correlation with users who have checked in at those locations. When calculating feature embeddings for users and locations, social relationships are also considered as attention signals. The similarity value between location and correlation between users will be exploited in the overall architecture of the recommendation model, which will employ graph convolution networks to generate recommendations with high precision and recall. The proposed model is implemented and executed on popular datasets, then compared to baseline models to assess its overall effectiveness.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.75-82
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• 2023

The main purpose of this study is to analyze the metacognition of digital library search behavior of college students and to provide a fundamental data for the designing a user-centered online information retrieval system to find more optimal search results. In order to achieve the purpose of this study, metacognition was classified into the five main categories, including schema-training, planning, monitoring, evaluation, and transfer, and a total of twenty subcategories were included. A total of 112 students participated in the online questionnaire. The collected data were analyzed using SPSS version 26, and it was found that there was a significant correlation between metacognition of college students and their digital library searching behavior. In particular, the digital library search experience was found to be the strongest factor to be considered as the most important variable in digital library design based on the aspect of user metacognition.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.400-405
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• 2006

In this paper, we present effective methods for music summarization which summarize music automatically. It could be used for sample music of on-line digital music provider or some music retrieval technology. When summarizing music, we use different two methods according to music length. First method is for finding sabi or chorus part of music which can be regarded as the most important part of music and the second method is for extracting several parts which are in different structure or have different mood in the music. Our proposed music summarization system is better than conventional system when structure of target music is explicit. The proposed method could generate just one important segment of music or several segments which have different mood in the music. Thus, this scheme will be effective for summarizing music in several applications such as online music streaming service and sample music for Tcommerce.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.3
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• pp.632-638
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• 2009

Probabilistic Latent Semantic Analysis has many applications in information retrieval and filtering, natural language processing, machine learning from text, and in related areas. In this paper, we propose an algorithm using weighted Probabilistic Latent Semantic Analysis Model to find the contextual phrases and opinions from documents. The traditional keyword search is unable to find the semantic relations of phrases, Overcoming these obstacles requires the development of techniques for automatically classifying semantic relations of phrases. Through experiments, we show that the proposed algorithm works well to discover semantic relations of phrases and presents the semantic relations of phrases to the vector-space model. The proposed algorithm is able to perform a variety of analyses, including such as document classification, online reputation, and collaborative recommendation.

• Journal of Korean Library and Information Science Society
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• v.30 no.3
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• pp.295-322
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• 1999

The purpose of this study is to identify and present the solution to the problems of KORMARC on Disc, which was produced by the National Library of Korea and is being distributed nationwide. Currently, KORMARC on Disc has reached the serious level of duplicates of input record, error on input data and noise of retrieval. Futhermore, input data is not in accordance with KORMARC Rules for Descriptive Cataloging, thus generating many problems. Of all thing, since current MARC system itself is based on manual system, it does not correspond effectively to the online environment. Accordingly, in order to elevate the quality of KORMARC database, current problems must be resolved, at the same time, korea Machine Readable Cataloging must be modified into a format, more suitable to Machine Readable environment. Consequently, the current study analyzes and identifies problems of data in KORMARC on Disc, at the same time, it examines currently used KORMARC Format and Korea machine Readable Cataloging Rules for descriptive Cataloging as to provide easier usage and guidelines for accurate data inputs.

• Journal of Plant Biotechnology
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• v.5 no.4
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• pp.197-200
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• 2003

Scalable Vector Graphics (SVG) has enabled a visually appealing, browser-based application for the display of Brassica sequences relative to Arabidopsis thaliana, and there are currently more than 70,000 B. napus Expressed Sequence Tags (ESTs) displayed. The client side of this browser is based on a Custom Graphical User Interface (CGUI) library which uses SVG, a new web graphics standard, to provide windowing functionality inside the web browser. This windowing functionality, combined with asynchronous data retrieval and client side rendering overcomes two of the key technology imposed drawbacks of current web based browsers: Fixed displays and frequent page reloads. The end result is an intuitive and enjoyable browsing experience. The browser is accessible online from the Brassica / Arabidopsis Genomics Initiative (http://brassica.agr.gc.ca). Inquiries about the browser should be directed to LewisCT@agr.gc.ca.

• Journal of the Korean Society for information Management
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• v.13 no.1
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• pp.19-43
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• 1996

The indexing languages and techniques were ~ u ~ e y e d for Korean textual databases, and retrieval effectivenesses of two indexing languages were evaluated in an online searching experiment. It was found that most of the Korean textual databases surveyed employ natural language indexing by either an automatic or a manual method, and that natural language indexing may outperform controlled language indexing if appropriate search strategies are employed.

• Journal of Information Management
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• v.23 no.4
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• pp.21-38
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• 1992

The purpose of this study is to grope for policy to foster the database industry of Korea. Then, this study suggests a definition, classifications and the industry structure of database, and presents the developing processes of both world and Korea database industry. Finally, the problems of domestic database industry of Korea are pointed out and the policy to foster it is suggested.

• Journal of the Korean Society for Library and Information Science
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• v.50 no.1
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• pp.133-159
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• 2016

The purpose of this study is to analyze related studies and domestic/international online reference cases, extract obstructive factors present in online reference services, and reveal whether or not there are differences in perception between the university librarian and the users. The results with respect to the failure of the resources revealed that while the user considers the quantitative / qualitative shortage of content as the greatest obstacle in the online reference service, librarians see the lack of human resources (Specialist Librarian / trained staff) in this light. Users think this is the least of the problems. In addition, other obstacles that are the most highly evaluated by librarians are, in order, the limitation of service because of copyright issues, the difficulty of information retrieval and complexity of methods of use, and a general lack of information in the reference services menu and missing information in the main menu. For the users the other most important obstacles were similar with the limitation of service because of copyright issues being highest, followed by the difficulty of access because of the confusion over service names, and the general lack of information in the reference services menu and missing information in the main menu.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1400-1418
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• 2020

In the development of commercial promotion, chatbot is known as one of significant skill by application of natural language processing (NLP). Conventional design methods are using bag-of-words model (BOW) alone based on Google database and other online corpus. For one thing, in the bag-of-words model, the vectors are Irrelevant to one another. Even though this method is friendly to discrete features, it is not conducive to the machine to understand continuous statements due to the loss of the connection between words in the encoded word vector. For other thing, existing methods are used to test in state-of-the-art online corpus but it is hard to apply in real applications such as telemarketing data. In this paper, we propose an improved chatbot design way using hybrid bag-of-words model and skip-gram model based on the real telemarketing data. Specifically, we first collect the real data in the telemarketing field and perform data cleaning and data classification on the constructed corpus. Second, the word representation is adopted hybrid bag-of-words model and skip-gram model. The skip-gram model maps synonyms in the vicinity of vector space. The correlation between words is expressed, so the amount of information contained in the word vector is increased, making up for the shortcomings caused by using bag-of-words model alone. Third, we use the term frequency-inverse document frequency (TF-IDF) weighting method to improve the weight of key words, then output the final word expression. At last, the answer is produced using hybrid retrieval model and generate model. The retrieval model can accurately answer questions in the field. The generate model can supplement the question of answering the open domain, in which the answer to the final reply is completed by long-short term memory (LSTM) training and prediction. Experimental results show which the hybrid word vector expression model can improve the accuracy of the response and the whole system can communicate with humans.