• Journal of KIISE:Computing Practices and Letters
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• v.15 no.5
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• pp.385-389
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• 2009

As a new community forming environment, the blog platform enables sharing of the resources in blogosphere through active information exchange. Many researches have been performed to recommend appropriate resources to users from vast amounts of blog resources. As one of the solutions OSEM defines the knowledge base in the blogosphere with ontology for effectively modeling it. In this paper, we propose a technique of converting the knowledge base into the OWL ontology for sharing it on the semantic web environment. An inference method is then applied to the OWL ontology for recommending interest blog communities. For this aim, a mapping method is offered and then SWRL inference and SPARQL query based on the ontology are employed to extract interest blog communities.

• Journal of the Korea Society of Computer and Information
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• v.19 no.4
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• pp.43-53
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• 2014

In this paper, we propose an ontology-based approach to measuring degree-of-interest in country by analyzing wikipedia usage data. First, we developed the degree-of-interest ontology called DOI ontology by extracting concept hierarchies from wikipedia categories. Second, we map the title of frequently edited articles into DOI ontology, and we measure degree-of-interest based on DOI ontology by analyzing wikipedia page views. Finally, we perform chi-square test of independence to figure out if interesting fields are independent or not by country. This approach shows interesting fields are closely related to each country, and provides degree of interests by country timely and flexibly as compared with conventional questionnaire survey analysis.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.3
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• pp.189-199
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• 2009

The amount of information on the Web is explosively growing as the Internet gains in popularity. However, only a small portion of the information on the Web is truly relevant or useful to the user. Thus, offering suitable information according to user demand is an important subject in information retrieval. In e-commerce, the recommender system is essential to revitalize commercial transactions, raise user satisfaction and loyalty towards the information provider. The existing recommender systems are mostly based on user data collected at servers, so user data are dispersed over several servers. Therefore, web servers that lack sufficient user behavior data cannot easily infer user preferences. Also, if the user visits the server infrequently, it may be hard to reflect the dynamically changing user's interest. This paper proposes a novel personalization system analyzing the user preference based on web documents that are accessed by the user on a user device. The system also identifies non-content blocks appearing repeatedly in the dynamically generated web documents, and adds weight to the keywords extracted from the hyperlink sentence selected by the user. Therefore, the system establishes at an early stage recommendation strategies for the web server that has little user data. Also, user profiles are generated rapidly and more accurately by identifying the information blocks. In order to evaluate the proposed system, this study collected web data and purchase history from users who have current purchase activity. Then, we computed the similarity between purchase data and the user profile. We confirm the accuracy of the generated user profile since the web page containing the purchased item has higher correlation than other item pages.

• The KIPS Transactions:PartB
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• v.12B no.2 s.98
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• pp.181-190
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• 2005

Developing wireless internet service and mobile devices, mechanisms for web service across are various. However, the existing web infrastructure and content were designed for desktop computers and arc not well-suited for other types of accesses, e.g. PDA or mobile Phone that have less processing power and memory, small screens, limited input facilities, or network bandwidth etc. Thus, there is a growing need for transcoding techniques that provide that ability to browse the web through mobile devices. However, previous researches on existing web contents transcoding are service provider centric, which does not accurately reflect the user's continuously changing interest. In this paper, we presents a transcoding technique involved in making existing news contents based on XML available via customized wireless service, mobile phone.

• Annual Conference of KIPS
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• 2008.05a
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• pp.475-478
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• 2008

본 연구에서는 채용정보를 제공하는 취업사이트에서 사용자가 관심 있게 생각하는 항목들이 무엇인가를 조사하였다. 연구에 필요한 항목조사는 랭키닷컴에서 제공하는 사이트별 순위정보를 기초로 하여 취업사이트에서 설문에 필요한 자료를 수집하여 온라인을 통하여 설문하였으며, 조사를 통하여 구직활동에서 필요한 정보가 무엇이며, 채용 정보 중에서 가장 많은 관심을 가지고 있는 정보가 무엇이며, 기업선택에 있어 어떤 요인이 중요하게 작용하는가를 분석하여, 채용정보중 지역, 근무시간, 급여조건, 휴가 및 휴일 등 카테고리정보와 세부적인 관심항목에서 유사한 관심도를 가지고 있는 것을 알 수 있었다.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10c
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• pp.547-549
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• 2001

대규모 온라인 게임과 같이 수많은 사용자를 수용하는 클라이언트/서버 방식 응용에서는 네트워크의 대역폭을 효율적으로 사용하는 것이 중요하다. 각 클라이언트의 관심영역에 해당하는 데이터만을 보내어 트래픽을 줄이는 방법을 관심영역 관리라 하며, 클래스기반, 영역 기반, 격자기반 등 여러 가지의 방법이 제안되어 있다. 본 논문에서는 작은 영역에서 거리 기반으로 관심영역을 정하는 관심영역 관리 기법을 제안하고, 이를 이용하여 참가자가 편중된 영역에서 생기는 트래픽 집중 현상을 해소하는 방법을 제안한다.

• 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 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.

• Journal of Korea Game Society
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• v.18 no.6
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• pp.69-82
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• 2018

The need of high quality VR contents has been steadily raised in recent years. Therefore, this study investigated the user's interest factors of VR game which is receiving the most attention among VR contents. We used STEAM review data and applied Text mining and Network analysis to perform this research. As a result, it was possible to confirm 4 word clusters related VR game users. Each cluster is named by 'presence', 'first person view game', 'auditory factor' and 'interaction'. This study has its meaning. First, user related research would be very helpful to develop high quality VR game. Second, it confirms that review data of VR game users can be structured, analyzed and used.

• Review of KIISC
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• v.12 no.2
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• pp.1-6
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• 2002

인터넷의 급속한 성장으로 인하여 안정적인 보안수준을 제공하면서 사용이 편리한 사용자 인증 시스템의 필요성이 대두되었다. 90년대까지 사용자 인증 수단으로 많이 사용되던 개인장치나 비밀번호 등은 분실 가능성 및 도용의 위험이 있어 보안이 중요한 환경에서는 사용상의 제약이 따른다. 그러므로 이러한 제약을 보완할 수 있는 생체정보를 이용한 사용자 인증에 대한 관심이 꾸준히 증가하고 있으나, 생체정보는 비밀번호와 같이 사용자가 임의로 변경할 수 없으므로 외부로 유출된다면 심각한 문제가 발생할 수 있다. 본 고에서는 생체정보를 중앙 데이터베이스에 저장하지 않고 사용자가 휴대할 수 있는 IC 카드에 저장하고, 생체정보를 이용한 사용자 인증 과정도 IC 카드 내부의 프로세서를 이용하여 수행하는 Match-on-Card 기술 개발에 관하여 설명한다.