• Journal of dental hygiene science
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• v.19 no.3
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• pp.190-197
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• 2019

Background: The Internet has advantages in terms of accessibility and amount of information, and the search for health information over the Internet is increasing exponentially. The purpose of this study is to analyze the information generated about some dental treatment on the internet by year. Methods: Naver Knowledge (JisikIn in Korean) which is an interactive search service was selected as the first search site in Korea. Scaling, wisdom tooth extraction, and endodontic treatment that can be paid by Korean health insurance were selected. Finally, 4,729 questions about scaling, 23,963 wisdom teeth extraction questions and 17,733 endodontic treatment questions were extracted. The question contents, the information about the questioner and the answerer, and an error of answers were investigated. Frequency analysis was used and chi-square test was used if necessary. Results: The most frequently asked questions were discomfort and dissatisfaction after the treatment. The need for treatment was the second in questions of the wisdom tooth extraction and endodontic treatment, but the health insurance benefit was the second in dental scaling. Most of the questioners didn't disclose personal information. The public answered the most in 2013~2014, but the highest percentage of the respondents was experts in 2017. Responses were mostly personal experience, but showed a tendency to decrease with years, and professional knowledge showed an increasing tendency. The error of the answer has also gradually decreased. Conclusion: Questions about dental care over the Internet are increasing exponentially, experts are responding increasingly, and errors in answers are decreasing. Nevertheless, it is necessary to pay attention to the related expert group to prevent misinformation.

• Herbal Formula Science
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• v.31 no.1
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• pp.67-79
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• 2023

Objectives : The purpose of this study was to confirm the consumption trends of Korean medicine for health food consumption of consumers by using the Naver DataLab Shopping Insight service. Methods : In this study, the search data for the category of Korean herbal ingredients in the health food field of Naver Datalab shopping insight site was collected and sorted in order of frequency from August 1st, 2017 to June 22nd, 2022. The frequently searched keywords were organized based on the inclusion of Korean Pharmacopoeia (KP), Korean Herbal Pharmacopoeia (KHP), and Food Code. Results : 67,804 keywords were collected, and the most frequent keywords appearing for more than 200 days among the top 500 were 827 (1.184%). Among the frequent keywords, there were 149 keywords related to traditional medicine names included in the KP and KHP, and five prescriptions were included. 60 keywords were not included in the KP and KHP, and the keyword with the highest search frequency was "kujibbongnamu" (Maclura tricuspidata). Conclusions : The findings of this study provide information on the consumer's interest in traditional korean medicine (TKM) and natural products (NP), and can be used as a basis for understanding the demand for TKM and NP in the online shopping market.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.265-274
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• 2021

In this paper, we propose a novel recommendation model based on Doc2vec using search keywords and product details. Until now, a lot of prior studies on recommender systems have proposed collaborative filtering (CF) as the main algorithm for recommendation, which uses only structured input data such as customers' purchase history or ratings. However, the use of unstructured data like online customer review in CF may lead to better recommendation. Under this background, we propose to use search keyword data and product detail information, which are seldom used in previous studies, for product recommendation. The proposed model makes recommendation by using CF which simultaneously considers ratings, search keywords and detailed information of the products purchased by customers. To extract quantitative patterns from these unstructured data, Doc2vec is applied. As a result of the experiment, the proposed model was found to outperform the conventional recommendation model. In addition, it was confirmed that search keywords and product details had a significant effect on recommendation. This study has academic significance in that it tries to apply the customers' online behavior information to the recommendation system and that it mitigates the cold start problem, which is one of the critical limitations of CF.

• The Journal of Society for e-Business Studies
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• v.16 no.3
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• pp.249-261
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• 2011

The rapid growth of e-business market makes new online companies to start and existing offline companies to join in this area. As the number of players of this market grows rapidly, the competition among them is very intense. Many companies invest huge resources to online marketing including search advertisement, email advertisement and banner advertisement. Because these traditional online marketing activities mainly focus on how to invite visitors to their web sites, ROI of these marketing activities are getting lower. Many companies are looking for a new marketing method to escape this situation. In this paper, we propose ROMS (Realtime Online Marketing System) which supports tools to improve conversion ratio of e-commerce sites, ROMS gathers behavioral data of visitors and analyzes it in realtime. ROMS supports live chats, visitor profiling, context analysis, event detection, and live marketing. With ROMS, personalized offers based on visitors' realtime context can be made for each visitor.

• Journal of Information Technology Applications and Management
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• v.25 no.2
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• pp.53-72
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• 2018

This empirical study explored characteristics that affect the usefulness of online reviews, in the China e-commerce platform, and implemented multiple regressions to find factors that significantly influence on product sales, ultimately. Till now, prior studies have continuously revealed what factor affects usefulness of online review or product sales, only in respective terms. The point of our study is that we built two-level regression models, thereby being able to comprehensively analyze these two different targets. Before plunging into running regressions, we carefully collected 192,764 online review data for 200 products extracted from the Jingdong, the second biggest e-commerce platform in China. Also, we gathered "review sentimental scores" variable from each review and used that one as a core variable in our regression model, thus we were able to implement both quantitative and qualitative research. The evidences from the two-level regression models showed that the extent to which a product is experience good positively affects both usefulness of a review and product sales, again the usefulness of a review contributes to product sales in sequence. Also, the property of experience good has interaction effect on both for two-level regression models. Our main findings highlight the importance of role of online review to business performance of e-commerce firms.

• International Journal of Contents
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• v.11 no.4
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• pp.44-55
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• 2015

There has been a significant paradigm shift in the book industry from print to digital, with the increased use of electronic books (e-books) on e-book readers. The major online booksellers and publishers are devoting their energies to the growth of the e-book market, resulting in an upward spiral in e-book usage, and a resultant increase in the number of downloaded e-books in an e-book reader library. However, there are comparatively few features for e-book management and search in most e-book reader libraries, particularly in smartphone environments. In addition, the user interfaces of e-book management in e-book readers are highly diverse, which has led to major usability issues. In this paper, we analyze user preferences for e-book management and search in the libraries of the five most commonly used e-readers for the Android smartphone platform via a questionnaire survey. Then, we suggest ideal alternatives in addition to user-friendly features based on user preferences for managing e-book libraries, to allow users to more easily browse collections, thereby enhancing the usability of e-book readers.

• International Journal of Internet, Broadcasting and Communication
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• v.8 no.2
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• pp.1-22
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• 2016

While many organizations believe that cloud computing has the potential to reduce operational cost by abstracting capital assets like data storage center and processing systems into a readily on demand available and affordable operating expenses, still many of these organizations are not aware of the factors determining the performance of cloud computing technology. This paper provides a systematic literature review focusing on the factors determining the performance of cloud computing. In trying to come up with this review, the following sources were searched for relevant articles: ScienceDirect, Scientific.Net, ACMDigital Library, IEEE Xplore, Springer, World Scientific Journal, Wiley Online Library, Academic Search Premier (via EBSCOHost) and EdITLib (Education & Information Technology Digital Library). In first search strategy, approximately 100 keywords related to the research domain like; "Cloud Computing" and "Cloud Services" were used. In second search strategy, 65 keywords more related to the research domain were selected. In the third search strategy, the primary materials were identified and classified according to the paper types (Journal or Conference), year of publication and so on. Based on this study, twenty (20) factors were found that determine the performance of cloud computing. The IT organization needs to consider these twenty (20) factors in order to adopt cloud computing.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.18 no.1
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• pp.169-187
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• 2007

This study investigated search interface of Korea children's library and suggested how to improve problems. This study researched 4 types search interface of 27 children's reading room, public/private children's Korea home page designs and International Children's Digital Library. To sum up, when interface designers design children's search interface, they should consider following factors. The size of letters are avaliable changed which little readers want to the size of letters. Avaliable to imput the keyboard or the mouse. The size of icons should design easy to click children in size. Children's interface should design user oriented.

• Journal of Intelligence and Information Systems
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• v.11 no.1
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• pp.153-167
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• 2005

In this paper, we consider the problem of exploring unknown environments with a mobile robot or an autonomous character agent. Traditionally, research efforts to address the space exploration problem havefocused on the graph-based space representations and the graph search algorithms. Recently EXPLORE, one of the most efficient search algorithms, has been discovered. It traverses at most min$min(mn, d^2+m)$ edges where d is the deficiency of a edges and n is the number of edges and n is the number of vertices. In this paper, we propose DFS-RTA* and DFS-PHA*, two real-time graph search algorithms for directing an autonomous agent to explore in an unknown space. These algorithms are all built upon the simple depth-first search (DFS) like EXPLORE. However, they adopt different real-time shortest path-finding methods for fast backtracking to the latest node, RTA* and PHA*, respectively. Through some experiments using Unreal Tournament, a 3D online game environment, and KGBot, an intelligent character agent, we analyze completeness and efficiency of two algorithms.

• Journal of KIISE:Software and Applications
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• v.37 no.8
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• pp.620-628
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• 2010

With the use of the Internet pervasive in everyday life, people are now able to retrieve a lot of information through the web. However, exponential growth in the quantity of information on the web has brought limits to online search engines in their search performance by showing piles and piles of unwanted information. With so much unwanted information, web users nowadays need more time and efforts than in the past to search for needed information. This paper suggests a method of using query expansion in order to quickly bring wanted information to web users. Popularity based Term Weight Mensuration better performance than the TF-IDF and Simple Popularity Term Weight Mensuration to experiments without changes of search subject. When a subject changed during search, Popularity based Term Weight Mensuration's performance change is smaller than others.