• Journal of KIISE:Software and Applications
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• v.33 no.12
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• pp.1062-1072
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• 2006

Recently, new intelligent service frameworks, such as ubiquitous computing are proposed. So, the necessity of adaptive agent system has been increased. In this paper, we propose an intelligent service agent to help that ubiquitous computing system offer user suitable service in ubiquitous computing environment. In order to offer user suitable uT-service, an intelligent service agent mediates the gap between the context information in uT-service system, and user preference is reflected in it. Therefore, we focus on following three components; the first is suitable multi agent framework-agent communication analysis and applicable method of inference engine, the second is uT-ontologies to describe various context information-context information sharing between agents and context information understanding between agents, the third is learning method of user profile to apply in uT-service system. This approach enables us to build adaptive uT-service system to offer suitable service according to user preference.

• Journal of Digital Convergence
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• v.10 no.1
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• pp.301-307
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• 2012

The development of mobile devices and the spread of wireless network help share and exchange information and resources more easily. The bond them to Cloud Computing technology help pay attention to "Mobile Cloud" service, so there have been being a lot of studies on "Mobile Cloud" service. Especially, the important of 'Personalization Service' which is customized for each user's preference and context has been increasing. In order to provide appropriate personalization services, it enables to recognize user's current state, analyze the user's profile like user's tendency and preference, and draw the service answering the user's request. Most existing frameworks, however, are not very suitable for mobile devices because they were proposed on the web-based. And other context information except location information among user's context information are not much considered. Therefore, this paper proposed the context-aware framework, which provides more suitable services by using user's context and profile.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.690-696
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• 2016

Search engines that rely on morphological matching of user query and web document content do not support individual interests. This research proposes a personalized web search scheme that returns the results that reflect the users' query intent and personal preferences. The performance of the personalized search depends on using an effective user profiling strategy to accurately capture the users' personal interests. In this study, the user profiles are the databases of topic words and customized weights based on the recent user queries and the frequency of topic words in click history. To determine the precise meaning of ambiguous queries and topic words, this strategy uses WordNet to calculate the semantic relatedness to words in the user profile. The experiments were conducted by installing a query expansion and re-ranking modules on the general web search systems. The results showed that this method has 92% precision and 82% recall in the top 10 search results, proving the enhanced performance.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.6
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• pp.343-357
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• 2007

In this paper, we propose the techniques for effective management of profiles that necessary to provide adaptation content to an user. The profiles must be configured the related information of the user and can be exchanged according to periodic/aperiodic or event among user device, profile repository, contents adaptation server and contents storage server for providing adaptation content to an user. The profiles also must be supplied the contents services providers that need profiles for the adapted contents services. To support those function, we propose the management technologies of profiles and design profile framework supporting those. The proposed management framework of profiles is supported the profiles that are configurated using the various user's information and is used the Web Services for exchanging and providing regardless of the various devices and platform. The dynamic configuration method, metadata configuration method, and profiles providing methods using weight for effective management in the framework also are applied. The result of evaluation the proposed management techniques show effective profiles processing.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.407-410
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• 1999

WWW is an important method for retrieving or providing informations. Not only the amount of information but also it is widely located on the web, it is difficult for users to get or search information. Furthermore, to use search engine is also inconvenient, because it just uses a keyword without concerning a user's interest. At this point, we propose a design of web agent that uses the automatic document categorization system and user's profile concerning with a user's interest, so the agent can actively provide a information.

• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.29-37
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• 2015

Nowadays, the user-centric application based web 2.0 has replaced the web 1.0. The users gain and provide information by interactive network applications. As a result, traditional approaches that only extract and analyze users' local document operating behavior and network browsing behavior to build the users' preference profile cannot fully reflect their interests. Therefore this paper proposed a preference analysis and indicating approach based on the users' communication information from MicroBlog, such as reading, forwarding and @ behavior, and using the improved PersonalRank method to analyze the importance of a user to other users in the network and based on the users' communication behavior to update the weight of the items in the user preference. Simulation result shows that our proposed method outperforms the ontology model, TREC model, and the category model in terms of 11SPR value.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.97-117
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• 2012

Nowadays, Internet users tend to do a variety of actions at the same time such as web browsing, social networking and multimedia consumption. While watching a video, once a user is interested in any product, the user has to do information searches to get to know more about the product. With a conventional approach, user has to search it separately with search engines like Bing or Google, which might be inconvenient and time-consuming. For this reason, a video annotation platform has been developed in order to provide users more convenient and more interactive ways with video content. In the future of smart TV environment, users can follow annotated information, for example, a link to a vendor to buy the product of interest. It is even better to enable users to search for information by directly discussing with friends. Users can effectively get useful and relevant information about the product from friends who share common interests or might have experienced it before, which is more reliable than the results from search engines. Social networking services provide an appropriate environment for people to share products so that they can show new things to their friends and to share their personal experiences on any specific product. Meanwhile, they can also absorb the most relevant information about the product that they are interested in by either comments or discussion amongst friends. However, within a very huge graph of friends, determining the most appropriate persons to ask for information about a specific product has still a limitation within the existing conventional approach. Once users want to share or discuss a product, they simply share it to all friends as new feeds. This means a newly posted article is blindly spread to all friends without considering their background interests or knowledge. In this way, the number of responses back will be huge. Users cannot easily absorb the relevant and useful responses from friends, since they are from various fields of interest and knowledge. In order to overcome this limitation, we propose a method to filter a user's friends for information search, which leverages semantic video annotation and social networking services. Our method filters and brings out who can give user useful information about a specific product. By examining the existing Facebook information regarding users and their social graph, we construct a user profile of product interest. With user's permission and authentication, user's particular activities are enriched with the domain-specific ontology such as GoodRelations and BestBuy Data sources. Besides, we assume that the object in the video is already annotated using Linked Data. Thus, the detail information of the product that user would like to ask for more information is retrieved via product URI. Our system calculates the similarities among them in order to identify the most suitable friends for seeking information about the mentioned product. The system filters a user's friends according to their score which tells the order of whom can highly likely give the user useful information about a specific product of interest. We have conducted an experiment with a group of respondents in order to verify and evaluate our system. First, the user profile accuracy evaluation is conducted to demonstrate how much our system constructed user profile of product interest represents user's interest correctly. Then, the evaluation on filtering method is made by inspecting the ranked results with human judgment. The results show that our method works effectively and efficiently in filtering. Our system fulfills user needs by supporting user to select appropriate friends for seeking useful information about a specific product that user is curious about. As a result, it helps to influence and convince user in purchase decisions.

• Journal of Korea Multimedia Society
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• v.13 no.10
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• pp.1453-1462
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• 2010

In this paper, a new program recommendation system is proposed to recommend user preferred VOD program in IPTV environment. A proposed system is implemented with collaborative filtering method. For a user profile which describes user program preference, a program preference, sub-genre preference, and US(user similarity) weight of the user neighborhood is averaged and updated every week. In order to evaluate system performance, real 24-weeks cable TV watching data provided by Nilson Research Corp. are modified to fit for IPTV broadcasting environment and the simulation result shows quite comparative quality of recommendation. The experimental results optimum performance when user similarity based weighting, five person per group and five recommendation programs are used.

• Journal of KIISE:Information Networking
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• v.30 no.4
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• pp.545-558
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• 2003

It is expected that per-user customized services are widely used in next generation Personal Communication Network. The ultimate goal for personalized service is the Virtual home Environment (VHE) providing ´same-look-and-feel´ services for the subscriber wherever he roams to. To provide personalized services for each call, per-user service profiles are frequently referenced, so efficient service profile management is essentially required. To realized the VHE, typically two schemes, can be employed; One is Intelligent Network based service control and the other is a full replication scheme that always replicates profile in user´s current zone. The first scheme is referred as Central scheme and th second scheme is the modified replication scheme of IMT-2000, we refer to as Follow-Me Replication Unconditional (FMRU). Since the Central scheme only depends on the service cal rate and the FMRU is merely dependent on the movement rate, it is apparent that FMRU scheme outperforms the Central scheme if the call to mobility ratio (CMR) is large, and vice versa. In this paper, we propose a new service profile replication schemes, Adaptive Follow-Me Replication (AFMR) that determine replication automatically according to the user´s CMR. We compared the performance of the AFMR with the non-adaptive Follow-Me Replication unconditional on Demand (FMRUD) scheme. Performance results indicate that as the CMR of a user changes AFMR adapts well compared to the existing schemes.

• Convergence Security Journal
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• v.8 no.4
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• pp.105-113
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• 2008

Mobile computing environment is known to be quite difficult to provide user with a stable Quality of Service (QoS) due to vehicle mobility nature. In order to protect the inherent characteristics of wireless network such as low bandwidth and high transmission delay along with the vehicle's mobility, many works are conducted to apply caching and prefetching methods. This paper presents a novel prefetching technique which is based on owner's profile. It is the scheme with the vehicle velocity, the visit frequency and resident time of specific region for vehicle owner's past given period, and the user profile which has owner's personal inclination about a certain place. The proposed scheme shown relatively superior performance in terms of the utilization ratio of prefetched information and the failure ratio of information retrieval than the previous methods.