• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.1-17
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• 2023

With the recent rapid development of ICT(Information and Communication Technology) and the popularization of digital devices, the size of the online market continues to grow. As a result, we live in a flood of information. Thus, customers are facing information overload problems that require a lot of time and money to select products. Therefore, a personalized recommender system has become an essential methodology to address such issues. Collaborative Filtering(CF) is the most widely used recommender system. Traditional recommender systems mainly utilize quantitative data such as rating values, resulting in poor recommendation accuracy. Quantitative data cannot fully reflect the user's preference. To solve such a problem, studies that reflect qualitative data, such as review contents, are being actively conducted these days. To quantify user review contents, text mining was used in this study. The general CF consists of the following three steps: user-item matrix generation, Top-N neighborhood group search, and Top-K recommendation list generation. In this study, we propose a recommendation algorithm that applies an extended similarity measure, which utilize quantified review contents in addition to user rating values. After calculating review similarity by applying TF-IDF, Word2Vec, and Doc2Vec techniques to review content, extended similarity is created by combining user rating similarity and quantified review contents. To verify this, we used user ratings and review data from the e-commerce site Amazon's "Health and Personal Care". The proposed recommendation model using extended similarity measure showed superior performance to the traditional recommendation model using only user rating value-based similarity measure. In addition, among the various text mining techniques, the similarity obtained using the TF-IDF technique showed the best performance when used in the neighbor group search and recommendation list generation step.

• KSCI Review
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• v.14 no.2
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• pp.215-224
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• 2006

Regarding a spam attack and the interception that a spinoff is largest among Vulnerability of VoIP at these papers study. Write scenario of a spam attack regarding VoIP Vulnerability, and execute Call spam. Instant Messaging spam, Presence spam attack. A spam attack is succeeded in laboratories, and prove. and confirm damage fact of a user in proposals of a spam interception way of VoIP service, 1) INVITE Request Flood Attack 2) Black/White list, 3) Traceback, 4) Black Hole-Sink Hole, 5) Content Filtering, 6) Consent based Communication, 7) Call act pattern investigation, 8) Reputation System Propose, and prove. Test each interception plan proposed in VoIP networks, and confirm security level of a spam interception. Information protection of VoIP service is enlarged at WiBro, BcN. and to realize Ubiquitous Security through result of research of this paper contribute, and may make.

• Journal of Information Technology and Architecture
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• v.10 no.2
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• pp.251-261
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• 2013

The appearance of various mobile Internet environment access to existing networks of mobile devices is easier to tell. In addition, mobile device users to use the wireless environment than a wired environment, user profile information is readily available features. Mobile devices have features that use alone. These characteristics of mobile devices to apply the personalization service is the best system. This paper proposes for mobile device users a personalized mobile music content recommendation service. This service propose to utilizes the user's access history information using time-weighting and collaborative filtering. Access history information can find out information of user interest. Using this information, consider the preference of music genre and time-weighted based on the recommendations makes the music. This method the problem of the traditional music recommendation system, point user's favorite music genre is changing over time do not consider that to solve the problem.

• Journal of the Korea Society of Computer and Information
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• v.11 no.5 s.43
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• pp.241-250
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• 2006

Regarding a spam attack and the interception that a spinoff is largest among weakness of VoIP service at these papers study. Write scenario of a spam attack regarding VoIP service, and execute Call spam, Instant Messaging spam, Presence spam attack. A spam attack is succeeded in laboratories, and prove, and confirm damage fact of a user in proposals of a spam interception way of VoIP service, 1) INVITE Request Flood Attack 2) Black/White list, 3) Traceback, 4) Black Hole-Sink Hole, 5) Content Filtering, 6) Consent based Communication, 7) Call act pattern investigation, 8) Reputation System Propose, and prove. Test each interception plan proposed in VoIP networks, and confirm security level of a spam interception. Information protection of VoIP service is enlarged at WiBro, BcN, and to realize Ubiquitous Security through result of research of this paper contribute, and may make.

• Journal of Biosystems Engineering
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• v.27 no.2
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• pp.151-160
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• 2002

Cow image processing technique would be useful not only for recognizing an individual but also for establishing the image database and analyzing the shape of cows. A cow (Holstein) has usually the unique speckle pattern. In this study, the individual recognition of cow was carried out using the speckle pattern and the content-based image retrieval technique. Sixty cow images of 16 heads were captured under outdoor illumination, which were complicated images due to shadow, obstacles and walking posture of cow. Sixteen images were selected as the reference image for each cow and 44 query images were used for evaluating the efficiency of individual recognition by matching to each reference image. Run-lengths and positions of runs across speckle area were calculated from 40 horizontal line profiles for ROI (region of interest) in a cow body image after 3 passes of 5$\times$5 median filtering. A similarity measure for recognizing cow individuals was calculated using Euclidean distance of normalized G-frame histogram (GH). normalized speckle run-length (BRL), normalized x and y positions (BRX, BRY) of speckle runs. This study evaluated the efficiency of individual recognition of cow using Recall(Success rate) and AVRR(Average rank of relevant images). Success rate of individual recognition was 100% when GH, BRL, BRX and BRY were used as image query indices. It was concluded that the histogram as global property and the information of speckle runs as local properties were good image features for individual recognition and the developed system of individual recognition was reliable.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.8C
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• pp.689-696
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• 2010

The goal of this paper is to present a novel method for protecting digital image using 2-D cellular automata transform (CAT). A copyright and transform coefficients are used to generate a new content-based copyright and an original digital image is distributed without any hidden copyright. The parameter, which is called gateway value, for 2-D CAT is consisted of rule number, initial configuration, lattice length, number of neighbors, and etc. Since 2-D CAT has various gateway values, it is more secure than conventional methods. The proposed algorithm is verified using attacked images such as filtering, cropping, JPEG compression, and rotation for robustness.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.1
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• pp.106-112
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• 2019

The Korea Copyright Commission has pursued copyright technology R&D projects to prevent illegal copying of comics and Webtoons. We developed a feature-based scanned comic filtering technology in order to apply technical measures to specific types of online service providers. We also developed technologies in order to monitor and identify illegally distributed comics on webhard sites and to monitor and identify illegally distributed webtoons. Even though all comic books posted on webhard sites are illegal, it is no trouble to download and access popular comics by accessing websites in foreign countries. Even under these circumstances, the comic and webtoon copyright protection technologies developed over the past six years have been used at all. In this paper, we examine what the problems are and find solutions to propose a copyright protection method for webtoons.

• KNOM Review
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• v.22 no.1
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• pp.52-59
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• 2019

As the video streaming service are supported by various devices, the amount of usage increases and efforts to improve the service from the viewpoint of users have continued. When a user watches a video, a response time occurs from input to playback, and if this response time becomes longer, the user's service satisfaction decreases. In this paper, we are proposing a method prefetching each user's preference video data obtained by analyzing user's past history record to the device for reducing the response time. We will show the result that prefetching data can improve the response time to 41% at most. And we analyzed real-video streaming viewing record and got each user's preferred video list. We investigated the change of response time according to a hit-ratio and amount of overhead data that was prefetched to the device, but not viewed. It was shown that as the hit-ratio grows bigger, the improvement of response time becomes more effective.

• Korean Journal of Materials Research
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• v.34 no.1
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• pp.12-20
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• 2024

This study successfully prepared high-porosity aluminosilicate fibrous porous ceramics through vacuum suction filtration using aluminosilicate fiber as the primary raw material and glass powder as binder, with the appropriate incorporation of glass fiber. The effects of the composition of raw materials and sintering process on the structure and properties of the material were studied. The results show that when the content of glass powder reached 20 wt% and the samples were sintered at the temperature of 1,000 ℃, strong bonds were formed between the binder phase and fibers, resulting in a compressive strength of 0.63 MPa. When the sintering temperatures were increased from 1,000 ℃ to 1,200, the open porosity of the samples decreased from 89.08 % to 82.38 %, while the linear shrinkage increased from 1.13 % to 10.17 %. Meanwhile, during the sintering process, a large amount of cristobalite and mullite were precipitated from the aluminosilicate fibers, which reduced the performance of the aluminosilicate fibers and hindered the comprehensive improvement in sample performance. Based on these conditions, after adding 30 wt% glass fiber and being sintered at 1,000 ℃, the sample exhibited higher compressive strength (1.34 MPa), higher open porosity (89.13 %), and lower linear shrinkage (5.26 %). The aluminosilicate fibrous porous ceramic samples exhibited excellent permeability performance due to their high porosity and interconnected three-dimensional pore structures. When the samples were filtered at a flow rate of 150 mL/min, the measured pressure drop and permeability were 0.56 KPa and 0.77 × 10^-6 m² respectively.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.29-56
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• 2021

Recently, various types of products have been launched with the rapid growth of the e-commerce market. As a result, many users face information overload problems, which is time-consuming in the purchasing decision-making process. Therefore, the importance of a personalized recommendation service that can provide customized products and services to users is emerging. For example, global companies such as Netflix, Amazon, and Google have introduced personalized recommendation services to support users' purchasing decisions. Accordingly, the user's information search cost can reduce which can positively affect the company's sales increase. The existing personalized recommendation service research applied Collaborative Filtering (CF) technique predicts user preference mainly use quantified information. However, the recommendation performance may have decreased if only use quantitative information. To improve the problems of such existing studies, many studies using reviews to enhance recommendation performance. However, reviews contain factors that hinder purchasing decisions, such as advertising content, false comments, meaningless or irrelevant content. When providing recommendation service uses a review that includes these factors can lead to decrease recommendation performance. Therefore, we proposed a novel recommendation methodology through CNN-based review usefulness score prediction to improve these problems. The results show that the proposed methodology has better prediction performance than the recommendation method considering all existing preference ratings. In addition, the results suggest that can enhance the performance of traditional CF when the information on review usefulness reflects in the personalized recommendation service.