• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.5
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• pp.121-127
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• 2008

User needs in residential environment have very complicated and variety connection with others. u-home system for the near future is need to be combined acceptance of exist user needs as well as needs on new technology relating with u-Home. The study proposes a User Behavior Analysis Framework - UBAF for applying the user needs to the system more efficiently and developing the system by classifying patterns for the needs based on date of user behavior analysis. UBAF is a developing framework getting the basic idea of combining system modeling methods on SE and user modeling methods considering on HCI. It will be applicable to develop the system with core user behaviors by applying a standard way on u-Home. For example, the study transforms information into knowledge the system modeling and user modeling with analyzing a scenario for indoor temperature controlling on u-Home.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.2972-2991
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• 2016

WLAN is the best choice in the place where complex network is hard to set up. Intelligent terminals are more and more assembled in some areas now. However, according to IEEE 802.11n/802.11ac, the access-point (AP) can only serve one user at a single frequency channel. The spectrum efficiency urgently needs to be improved. In theory, AP with multi-antenna can serve multiple users if these users do not interfere with each other. In this paper, we propose a user clustering scheme that could achieve multi-user selection through the mutual cooperation among users. We focus on two points, one is to achieve multi-user communication with multiple antennas technique at a single frequency channel, and the other one is to use a way of distributed users' collaboration to determine the multi-user selection for user clustering. Firstly, we use the CSMA/CA protocol to select the first user, and then we set this user as a source node using users' cooperation to search other proper users. With the help of the users' broadcast cooperation, we can search and select other appropriate user (while the number of access users is limited by the number of antennas in AP) to access AP with the first user simultaneously. In the network node searching, we propose a maximum degree energy routing searching algorithm, which uses the shortest time and traverses as many users as possible. We carried out the necessary analysis and simulation to prove the feasibility of the scheme. We hope this work may provide a new idea for the solution of the multiple access problem.

• Journal of the Korea Society of Computer and Information
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• v.9 no.2
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• pp.131-138
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• 2004

Considering international trends and foreign cases, it can be easily expected that web accessibility issue is becoming more and more important. While information technology has changed Korean society rapidly and widely, there are many People who have difficulties in using information services such as the elderly and persons with disabilities. One of the big barriers they face is the lack of accessibility of web services. These social problems have been rarely studied in Korea but surface as very import subjects to be addressed concerning IT and welfare policy. The objective of this study is to ensure web accessibility right for visually handicapped and reduce digital divide through development of a recommendation guideline of mobile internet user interface. In this study the trends of politics and laws related to web accessibility in developed countries are surveyed and some advisable recommendation guidelines of mobile internet user interface for visually handicapped to improve web accessibility are proposed.

• KIISE Transactions on Computing Practices
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• v.23 no.1
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• pp.65-73
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• 2017

Advances in Internet of Things Technology lead to the increasing number of daily-life things that are interconnected over the Internet. Also, several smart services are being developed by utilizing the connected things. Among the daily-life things surrounding user, the mirror can supports broad range of functionality and expandable service as it plays various roles in daily-life. Recently, various smart mirrors have been launched in certain places where people with specific goals and interests meet. However, most mirrors give the user limited information. Therefore, we designed and implemented a smart mirror that can support customized service. The proposed smart mirror utilizes information provided by other existing internet services to give user dynamic information as real_time traffic information, news, schedule, weather, etc. It also supports recommendation service based on user usage information.

• Journal of Internet Computing and Services
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• v.17 no.3
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• pp.1-10
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• 2016

Information and network technology become the rapid development, so various online services supplied by multimedia systems are provided through the Internet. Because of intrinsic open characteristic on Internet, network systems need to provide the data protection and the secure authentication. So various researchers including Das, An, and Li&Hwang proposed the biometric-based user authentication scheme but they has some security weakness. To solve their problem, Li et al. proposed new scheme using fuzzy extraction, but it is weak on off-line password attack, authentication without biometrics, denial-of-service and insider attack. So, we proposed security enhanced user authentication scheme with key agreement to address the security problem of authentication schemes.

• Journal of Internet Computing and Services
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• v.18 no.6
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• pp.93-100
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• 2017

In multi-media, multi-channel era, video viewing using various digital devices via the Internet, not the existing broadcasting network, is emerging as a new broadcasting viewing behavior. OTT service is regarded as the main service of this change of viewing behavior. It is a video service that can seamlessly use any content desired by the user at any time, at any time, any device, any contents, if the Internet connection is available. The purpose of this study is to investigate the factors affecting the satisfaction of OTT service by applying the technology acceptance model (TAM). As a result of analyzing through 303 questionnaires of the early users of OTT service, social pressure, perceived popularity, perceived cost, user reputation, individual innovation, and esthetics set as external factors in this study are partially affects perceived usefulness, perceived ease of use, and perceived enjoyment. In addition, perceived usefulness, ease of use, and enjoyment are directly influencing satisfaction. Based on these results, we discuss the theoretical and practical implications and propose future research direction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1168-1188
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• 2018

Social Network Aggregators are used to maintain and manage manifold accounts over multiple online social networks. Displaying the Activity feed for each social network on a common dashboard has been the status quo of social aggregators for long, however retrieving the desired data from various social networks is a major concern. A user inputs the query desiring the specific outcome from the social networks. Since the intention of the query is solely known by user, therefore the output of the query may not be as per user's expectation unless the system considers 'user-centric' factors. Moreover, the quality of solution depends on these user-centric factors, the user inclination and the nature of the network as well. Thus, there is a need for a system that understands the user's intent serving structured objects. Further, choosing the best execution and optimal ranking functions is also a high priority concern. The current work finds motivation from the above requirements and thus proposes the design of a query processing system to retrieve information from social network that extracts user's intent from various social networks. For further improvements in the research the machine learning techniques are incorporated such as Latent Dirichlet Algorithm (LDA) and Ranking Algorithm to improve the query results and fetch the information using data mining techniques.The proposed framework uniquely contributes a user-centric query retrieval model based on natural language and it is worth mentioning that the proposed framework is efficient when compared on temporal metrics. The proposed Query Processing System to Retrieve Information from Social Network (QPSSN) will increase the discoverability of the user, helps the businesses to collaboratively execute promotions, determine new networks and people. It is an innovative approach to investigate the new aspects of social network. The proposed model offers a significant breakthrough scoring up to precision and recall respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3335-3356
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• 2015

In this paper, we analyze the connectivity of cognitive radio ad-hoc networks in a log-normal shadow fading environment. Considering secondary user and primary user's locations and primary user's active state are randomly distributed according to a homogeneous Poisson process and taking into account the spectrum sensing efficiency of secondary user, we derive mathematical models to investigate the connectivity of cognitive radio ad-hoc networks in three aspects and compare with the connectivity of ad-hoc networks. First, from the viewpoint of a secondary user, we study the communication probability of that secondary user. Second, we examine the possibility that two secondary users can establish a direct communication link between them. Finally, we extend to the case of finding the probability that two arbitrary secondary users can communicate via multi-hop path. We verify the correctness of our analytical approach by comparing with simulations. The numerical results show that in cognitive radio ad-hoc networks, high fading variance helps to remarkably improve connectivity behavior in the same condition of secondary user's density and primary user's average active rate. Furthermore, the impact of shadowing on wireless connection probability dominates that of primary user's average active rate. Finally, the spectrum sensing efficiency of secondary user significantly impacts the connectivity features. The analysis in this paper provides an efficient way for system designers to characterize and optimize the connectivity of cognitive radio ad-hoc networks in practical wireless environment.

• Journal of Internet Computing and Services
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• v.15 no.5
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• pp.73-82
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• 2014

SNS becomes a recent issue, and many researches in various kinds of field are being done by taking advantage of it. Especially, there are many researches existed on the system that finds user's interest and makes recommendation based on multiple social data generated on the SNS. User's interest is not only revealed from the user's writing but also from the user's relationship with friends. This study proposes a recommendation method that extracts user's interest by using social relationship and its categorization applies it to the recommendation. In this way, it can recommend user's interest with category based on the writings by the user and furthermore it can apply the user's relationship with his/her friends for more accurate recommendation. In addition, if necessary, the recommendation can be made by extracting any interest shared between the user and specific friends. Through experiments, we show that our method using social category can produce satisfactory result.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3798-3814
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• 2022

Social recommendation algorithm can alleviate data sparsity and cold start problems in recommendation system by integrated social information. Among them, matrix-based decomposition algorithms are the most widely used and studied. Such algorithms use dot product operations to calculate the similarity between users and items, which ignores user's potential preferences, reduces algorithms' recommendation accuracy. This deficiency can be avoided by a metric learning-based social recommendation algorithm, which learns the distance between user embedding vectors and item embedding vectors instead of vector dot-product operations. However, previous works provide no theoretical explanation for its plausibility. Moreover, most works focus on the indirect impact of social friends on user's preferences, ignoring the direct impact on user's rating preferences, which is the influence of user rating preferences. To solve these problems, this study proposes a user bias drift social recommendation algorithm based on metric learning (BDML). The main work of this paper is as follows: (1) the process of introducing metric learning in the social recommendation scenario is introduced in the form of equations, and explained the reason why metric learning can replace the click operation; (2) a new user bias is constructed to simultaneously model the impact of social relationships on user's ratings preferences and user's preferences; Experimental results on two datasets show that the BDML algorithm proposed in this study has better recommendation accuracy compared with other comparison algorithms, and will be able to guarantee the recommendation effect in a more sparse dataset.