• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3714-3732
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• 2019

With the rapid development of network, Intrusion Detection System(IDS) plays a more and more important role in network applications. Many data mining algorithms are used to build IDS. However, due to the advent of big data era, massive data are generated. When dealing with large-scale data sets, most data mining algorithms suffer from a high computational burden which makes IDS much less efficient. To build an efficient IDS over big data, we propose a classification algorithm based on data clustering and data reduction. In the training stage, the training data are divided into clusters with similar size by Mini Batch K-Means algorithm, meanwhile, the center of each cluster is used as its index. Then, we select representative instances for each cluster to perform the task of data reduction and use the clusters that consist of representative instances to build a K-Nearest Neighbor(KNN) detection model. In the detection stage, we sort clusters according to the distances between the test sample and cluster indexes, and obtain k nearest clusters where we find k nearest neighbors. Experimental results show that searching neighbors by cluster indexes reduces the computational complexity significantly, and classification with reduced data of representative instances not only improves the efficiency, but also maintains high accuracy.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.809-820
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• 2021

The study aimed to investigate the impact of sectoral bank credit facilities provided by commercial banks on the non-oil economic growth in Saudi Arabia. Bank credit facilities are given for nine economic sectors: agriculture, manufacturing, mining, electricity and water, health services, construction, wholesale and retail trade, transportation and communications, services, and finance sector. The study employs annual data from 1970 to 2019. The study employs the Autoregressive Distributed Lag (ARDL) approach to identify the long-run and short-run dynamics relationships among the variables. The main results reveal that the overall impact of total bank credit has a significant and positive effect on non-oil economic growth in KSA. The results revealed that the effect of bank credit on the non-oil GDP growth in the short and long run was uneven. The study finds that all sectors have a positive and significant impact in the long run, except for the agricultural and mining sectors. Likewise, all sectors have a positive and significant impact in the short run, except for construction, finance, services, and transportation & communications. As a result, bank credit facilities in different sectors have played an important role in enhancing the non-oil economic growth in the KSA.

• The Journal of Information Systems
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• v.31 no.2
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• pp.1-18
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• 2022

Purpose Customer review is a major factor in choosing certain restaurants. This study investigates the key factors affecting customer's evaluation about restaurants. With the recent intensification of competition among restaurants in the service industry, the analysis results are expected to provide in-depth insights for enhancing customer experiences. Design/methodology/approach We collected information and reviews provided at the restaurants in the Kakao Map platform. The information collected is based on the information of 3,785 restaurants in Daegu registered on Kakao Map. Based on the information collected, seven independent variables, including number of rating registered, number of reviews, presence or absence of safe restaurants, presence or absence of a posting about holding facilities, presence or absence of a posting about business hours, presence or absence of a posting about hashtags, and presence or absence of break times, were used. Dependent variable is restaurant rating. Multiple regression between independent variables and restaurant rating was carried out. Findings The results of the study confirmed that number of rating registered, presence or absence of a posting about business hours, and presence or absence of a posting about hash tags have an positive effects on the restaurant rating. The number of reviews had a negative effect on the restaurant rating. In addition, in order to confirm the role of customer's reviews, we carried out LDA topic modeling. We divided the topics into the positive review and the negative reviews.

• International Journal of Knowledge Content Development & Technology
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• v.12 no.4
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• pp.41-65
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• 2022

This study would understand the overall perception of our society about public libraries, analyzing the texts related to public libraries, utilizing the semantic connection network & sentiment analysis. For this purpose, this study collected data from the last five years with keywords, 'Library' and 'Lifelong Learning Center' from January 1, 2016 through November 30, 2020 through the blogs and cafés of major domestic portal sites. With the collected data, text mining, centrality of keywords, network structure, structural equipotentiality, and sensitivity analyses were conducted. As a result of the analysis, First, 'reading' and 'book' were identified as representative keywords that form the social perception of public libraries. Second, it turned out that there were keywords related to the use of the library and the untact service due to the recent spread of COVID-19. Third, in seeking a plan for the development of public libraries through the keywords drawn to have positive meanings, it is necessary to create continuous services that can form a new image of the library, breaking away from the existing fixed role and image of the library and increase the convenience of use. Fourth, facilities and facilities for library services were recognized from a neutral point of view. Fifth, the spread of infectious diseases, social distancing, and temporary closure and closure of libraries are negatively related to public libraries, and awareness of librarians has been identified as negative keywords.

• Geomechanics and Engineering
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• v.34 no.1
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• pp.51-67
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• 2023

In this research, the degradation rate of physical properties of the Angouran pit bedrock (calc-schist) is first investigated under the specific numbers of freeze-thaw (F-T) cycles. Then, the durability of calc-schist specimens against the F-T cycle number (N) is examined considering the mechanical parameters, and using the decay function and half-time techniques. For this purpose, point load strength (I_S(50)), second durability index (I_d2), Brazilian tensile strength (BTS), and compressive (V_P) and shear (V_S) wave velocities of calc-schist specimens are measured after 0, 7, 15, 40, and 75 N. For comparing the degradation rate of mechanical properties of available rock types on the Angouran mine walls, these tests are also carried out on the limestone and amphibolite schist specimens beside the calc-schist. According to test results, the exponential regression models are developed between the mechanical parameters of rock specimen's and N variable. Also, the long-term durability of each rock type versus N is studied using the decay function and half-time techniques. Results indicated that the degradation rate differs for the above rock types in which amphibolite schist and calc-schist specimens have the highest and least resistance against the N, respectively. The obtained results from this study can play a key role in the optimal design of the mine's final walls.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2020.06a
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• pp.222-223
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• 2020

Recently, as the era of economic cooperation on the Korean Peninsula approaches, the role of the building sector, such as humanitarian reorganization of North Korean housing, is increasing. The purpose of this study is to find out the current location of North Korean housing standards through the North Korean Housing Survey. For the survey, a survey was conducted through 79 North Korean defectors. The main construction methods of North Korean housing are reinforced concrete, steel framed, wooden framed, masonry, and reinforced concrete walled and prefabricated. The residential environment satisfaction items consist of durability, waterproof, heating, ventilation, heat insulation, air tightness, mining, soundproofing, disaster safety, fire safety, and crime prevention. The result is as follows. The housing construction method in North Korea, which lived at that time, consisted of 21 people (30.88%) of reinforced concrete frames, 18 people (26.47%) of wooden frames, 17 people (25%) of masonry walls, 5 people of prefabricated structures (7.35%), and reinforced concrete. Two people (2.94%) were walled. Among these, the wooden frame type had the lowest satisfaction level for each item, and the reinforced concrete had a high level of dissatisfaction in the items of heating, confidentiality, and disaster safety, and the other item had a high level of satisfaction. The masonry wall type has a relatively high satisfaction level in terms of insulation, confidentiality, mining, and disaster safety.

• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.5
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• pp.943-958
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• 2023

This study explores the sneakerhead subculture through the lens of subcultural capital, primarily focusing on online community interactions. The analysis utilizes text mining techniques and netnographic research methods to examine textual data extracted from the online sneakerhead community and aims to elucidate manifestations of subcultural capital within the subculture. The findings underscore several key points: Firstly, shared experiences cultivated by the collective consciousness of subcultural capital foster solidarity among members. Secondly, ongoing validation of authenticity and comprehension of sneakers' cultural significance are member requirements. Subsequently, exhibiting greater levels of subcultural capital empowers members, resulting in hierarchical structures both within and beyond the community. Fourthly, resale-driven sneaker commercialization yields positive outcomes, including individual profit and cultural expansion, yet also brings negative consequences, such as market distortion and intra-community conflict. Lastly, the online community fills a pivotal role in dictating subcultural trends, effectively functioning as an institutional network. Given sneakers' enduring status as a fashion phenomenon, further examination of in this realm is warranted.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.1
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• pp.71-79
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• 2007

Recent advances in the internet infrastructure have resulted in a large number of huge Web sites and portals worldwide. These Web sites are being visited by various types of users in many different ways. Among all the web page access sequences from different users, some of them occur so frequently that may need an attention from those who are interested. We call them frequent access patterns and access sequences that can be frequent the candidate patterns. Since these candidate patterns play an important role in the incremental Web mining, it is important to efficiently generate, add, delete, and search for them. This thesis presents a novel tree structure that can efficiently store the candidate patterns and a related set of algorithms for generating the tree structure, adding new patterns, deleting unnecessary patterns, and searching for the needed ones. The proposed tree structure has a kind of the 3 dimensional link structure and its nodes are layered.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.11
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• pp.2866-2879
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• 2012

Among the various security threats in online games, the use of game bots is the most serious problem. Previous studies on game bot detection have proposed many methods to find out discriminable behaviors of bots from humans based on the fact that a bot's playing pattern is different from that of a human. In this paper, we look at the chatting data that reflects gamers' communication patterns and propose a communication pattern analysis framework for online game bot detection. In massive multi-user online role playing games (MMORPGs), game bots use chatting message in a different way from normal users. We derive four features; a network feature, a descriptive feature, a diversity feature and a text feature. To measure the diversity of communication patterns, we propose lightly summarized indices, which are computationally inexpensive and intuitive. For text features, we derive lexical, syntactic and semantic features from chatting contents using text mining techniques. To build the learning model for game bot detection, we test and compare three classification models: the random forest, logistic regression and lazy learning. We apply the proposed framework to AION operated by NCsoft, a leading online game company in Korea. As a result of our experiments, we found that the random forest outperforms the logistic regression and lazy learning. The model that employs the entire feature sets gives the highest performance with a precision value of 0.893 and a recall value of 0.965.

• Journal of Multimedia Information System
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• v.1 no.1
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• pp.67-75
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• 2014

Nowadays as video services grow rapidly, it is important for the service providers to provide customized services. Video ranking plays a key role for the service providers to attract the subscribers. In this paper we propose a weekly video ranking mechanism based on the quantified user engagement. The traditional QoE ranking mechanism is relatively subjective and usually is accomplished by grading, while QoS is relatively objective and is accomplished by analyzing the quality metrics. The goal of this paper is to establish a ranking mechanism which combines the both advantages of QoS and QoE according to the third-party data collection platform. We use data mining method to classify and analyze the collected data. In order to apply into the actual situation, we first group the videos and then use the regression tree and the decision tree (CART) to narrow down the number of them to a reasonable scale. After that we introduce the analytic hierarchy process (AHP) model and use Elo rating system to improve the fairness of our system. Questionnaire results verify that the proposed solution not only simplifies the computation but also increases the credibility of the system.