• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.21 no.4
• /
• pp.183-188
• /
• 2021

Collaborative filtering based recommender systems are currently indispensable function of commercial systems in various fields, being a useful service by providing customized products that users will prefer. However, there is a high possibility that the prediction of preferrable products is inaccurate, when the user's rating data are insufficient. In order to overcome this drawback, this study suggests a stepwise method for prediction of product ratings. If the application conditions of the prediction method corresponding to each step are not satisfied, the method of the next step is applied. To evaluate the performance of the proposed method, experiments using a public dataset are conducted. As a result, our method significantly improves prediction and precision performance of collaborative filtering systems employing various conventional similarity measures and outperforms performance of the previous methods for solving rating data sparsity.

• Proceedings of the IEEK Conference
• /
• 2003.07c
• /
• pp.2649-2652
• /
• 2003

In this Paper, an Audio-Visual Teaching aid (AVTA) for use in a classroom and with Internet is presented. A system, which was designed and tested, consists of a wireless Microphone system, Text to Speech conversion Software, Noise filtering circuit and a Computer. An IBM compatible PC with sound card and Network Interface card and a Web browser and a voice and text messenger service were used to provide slightly delayed text and also voice over the internet for remote teaming, while providing scrolling text from a real time lecture in a classroom. The motivation for design of this system, was to aid Korean students who may have difficulty in listening comprehension while have, fairly good reading ability of text. This application of this system is twofold. On one hand it will help the students in a class to view and listen to a lecture, and on the other hand, it will serve as a vehicle for remote access (audio and text) for a classroom lecture. The project provides a simple and low cost solution to remote learning and also allows a student to have access to classroom in emergency situations when the student, can not attend a class. In addition, such system allows the student in capturing a teacher's lecture in audio and text form, without the need to be present in class or having to take many notes. This system will therefore help students in many ways.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2022.05a
• /
• pp.385-387
• /
• 2022

With the tremendous rise in popularity of the Internet and technological advancements, many news keeps generating every day from multiple sources. As a result, the information (News) on the network has been highly increasing. The critical problem is that the volume of articles or news content can be overloaded for the readers. Therefore, the people interested in reading news might find it difficult to decide which content they should choose. Recommendation systems have been known as filtering systems that assist people and give a list of suggestions based on their preferences. This paper studies a personalized news recommendation system to help users find the right, relevant content and suggest news that readers might be interested in. The proposed system aims to build a hybrid system that combines collaborative filtering with content-based filtering to make a system more effective and solve a cold-start problem. Twitter social media data will analyze and build a user's profile. Based on users' tweets, we can know users' interests and recommend personalized news articles that users would share on Twitter.

• Journal of Internet Computing and Services
• /
• v.14 no.5
• /
• pp.59-67
• /
• 2013

In this paper, we propose the LAR_CF, latent attribute rating-based collaborative filtering, that is robust to data sparsity problem which is one of traditional problems caused of decreasing rating prediction accuracy. As compared with that existing collaborative filtering method uses a preference rating rated by users as feature vector to calculate similarity between objects, the proposed method improves data sparsity problem using unique attributes of two target objects with existing explicit preference. We consider MovieLens 100k dataset and its item attributes to evaluate the LAR_CF. As a result of artificial data sparsity and full-rating experiments, we confirmed that rating prediction accuracy can be improved rating prediction accuracy in data sparsity condition by the LAR_CF.

• The KIPS Transactions:PartB
• /
• v.16B no.1
• /
• pp.85-92
• /
• 2009

As World Wide Web is more popularized nowadays, the environment is flooded with the information through the web pages. However, despite such convenience of web, it is also creating many problems due to uncontrolled flood of information. The pornographic, violent and other harmful information freely available to the youth, who must be protected by the society, or other users who lack the power of judgment or self-control is creating serious social problems. To resolve those harmful words, various methods proposed and studied. This paper proposes and implements the protecting system that it protects internet youth user from harmful contents. To classify effective harmful/harmless contents, this system uses two step classification systems that is harmful word filtering and SVM learning based filtering. We achieved result that the average precision of 92.1%.

• The KIPS Transactions:PartD
• /
• v.10D no.1
• /
• pp.125-132
• /
• 2003

The Internet reservation service is one of the most utilized internet services, specifically the agent efficiently supports this reservation services. The Agent will replace the repetitious reservation process and selectively offering the most proper service information. In this study, the user assisting agent system that can enable people to make reservation of public transportations through the internet is designed and implemented. This system consists of multiple agents that are Interface agent, 4ask agents and filtering agent. The interface agent is an arbitrator of this system that analyzes user's demand and integrate agent's result. And it has user-adaptive capability using case-based reasoning. There are three task agents if this system, it executes information gathering and information-change monitoring of each. Filtering agent extracts information only about reservation status in gathered information. Finally, this system is to offer integrated information of the reservation status about train and airplane and execute the simple-repetitious works for the reservation instead of user by agents.

• Journal of Information Technology Applications and Management
• /
• v.20 no.3_spc
• /
• pp.219-230
• /
• 2013

Real time accessiblity and agility in Ubiquitous-commerce is required under ubiquitous computing environment. The Research has been actively processed in e-commerce so as to improve the accuracy of recommendation. Existing Collaborative filtering (CF) can not reflect contents of the items and has the problem of the process of selection in the neighborhood user group and the problems of sparsity and scalability as well. Although a system has been practically used to improve these defects, it still does not reflect attributes of the item. In this paper, to solve this problem, We can use a implicit method which is used by customer's data and purchase history data. We propose a new clustering method of weighted preference for customer using k-means clustering and Bayesian network in order to improve the accuracy of recommendation. To verify improved performance of the proposed system, we make experiments with dataset collected in a cosmetic internet shopping mall.

• The Journal of Society for e-Business Studies
• /
• v.7 no.3
• /
• pp.203-218
• /
• 2002

According as development of networks and increasing on Internet service, For the performance increase of K4 Firewall require that hardware be installed of 2 CPU or 4 CPU instead of 1 CPU. Output of performance test among 1CPU, 2CPU, and 4CPU of K4 Firewall system has not any efficient about increasing multiple CPUs. K4 Firewall put performance on setting on demon of packet filtering rules and Network Address Translate and Authentication and Proxy services. Performance results that setting after security rules are less 2％ Packet Filtering, 8％-11％ NAT, 18％-20％ Proxy and Authentication services than setting before security rules on K4 Firewall System. NAT and Proxy service have decrease of performance. This performance result comes in useful for research and development on K4 Firewall System.

• Journal of the Korea Computer Industry Society
• /
• v.4 no.10
• /
• pp.571-580
• /
• 2003

A intercepting program of Black List Filtering System is widely used for blocking the harmful information in the internet. Hut The Black List Filtering System give rise to reduce the performance of Client PC. In this thesis the author proposes the good way to solve a problem of the Black List Filtering System. Keep to the point that is puting the black List into The Black List Serve on Client/server Environment and building Black List into Client PC in use of revisiting pattern of web-user. The best effect that tried to Solve the problem in the experiment concerning the thesis is presented not only to maintain the performance of Client PC, but also to improve the speed of performance of Client PC.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.5
• /
• pp.1137-1143
• /
• 2015

Sensitive internal information has been transmitted in a variety of services of Internet environment, but almost users do not know what internal information is sent. In this paper, we intend to develop a new filtering system that continuously monitors the sensitive information in outbound network packets and notifies the internal user whether or not to expose. So we design a filtering system for sensitive information and analyze the implementation results. Thus users visually can check whether disclosure of the important information and drop the corresponding packets by the proposed system. The results of this study can help decrease cyber threats various targeting internal information of company by contributing to prevent exposure of sensitive internal information.