• Journal of the Korean Society for Library and Information Science
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• v.45 no.2
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• pp.185-207
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• 2011

In the current information environment, many approaches have been adopted to represent and organize information resources. Among these approaches, folksonomy using tags is now being used in knowledge representation and organization. Although it may be an efficient approach to overcome the limitations of previous approaches, there are several problems in assigning tags such as ambiguity, inconsistency, and polysemy that limit efficient information organization. This research proposes a conceptual framework for the control of semantics of tags through linking up with bibliographic records in order to maximize the efficiency and minimize the limitations of folksonomy tags.

• Journal of KIISE
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• v.43 no.10
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• pp.1165-1172
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• 2016

In cloud storage environment, deduplication enables efficient use of the storage. Also, in order to save network bandwidth, cloud storage service provider has introduced client-side deduplication. Cloud storage service users want to upload encrypted data to ensure confidentiality. However, common encryption method cannot be combined with deduplication, because each user uses a different private key. Also, client-side deduplication can be vulnerable to security threats because file tag replaces the entire file. Recently, proof of ownership schemes have suggested to remedy the vulnerabilities of client-side deduplication. Nevertheless, client-side deduplication over encrypted data still causes problems in efficiency and security. In this paper, we propose a secure and practical client-side encrypted data deduplication scheme that has resilience to brute force attack and performs proof of ownership over encrypted data.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.24-27
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• 2008

As shown in Wikipedia, tagging or cross-linking through major key-words improves the readability of documents. Recently, the Semantic Web rises the importance of social tagging as a key feature of the Web 2.0 and Tag Cloud has emerged as its crucial phenotype. In this paper we provides an efficient method of automated keyword tagging based on controlled term collection, where the computational complexity of O(mN) - if pattern matching algorithm is used - can be reduced to O(mlogN) - if Information Retrieval is adopted - while m is the length of target document and N is the total number of candidate terms to be tagged. The result shows that IR-based tagging speeds up 5.6 times compared with fast pattern matching algorithm.

• Journal of Internet Computing and Services
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• v.8 no.5
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• pp.1-10
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• 2007

Recently, the web 2.0 services which appear by exponential extension of the Internet can be expressed with the changes in the quality of structural evolution and in the quantity of increasing users. The structural base is in user participational architecture, the web 2.0 services such as Blog, UCC, SNS(Social Networking Service), Mash-up, Long tail, etc. play a important role in organization of web, and grouping and searching of user participational data in web 2.0 is broadly used by folksonomy. Folksonomy is a new form that categorizes by tags, not classic taxonomy skill. it is made by user participation. Searching based on tag is now done by a simple text or a tag cloud method. But searching to consider and express the relations among each tags is imperfect yet. Thus, this paper provides the relational searching based on tags using the relational graph of tags. It should improve the trust of the searching and provide the convenience of the searching.

• Journal of Internet Computing and Services
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• v.14 no.2
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• pp.1-13
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• 2013

Recent advance and popularization of smart devices and web application services based on cloud computing have made end-users to directly produce and, at the same time, consume the image contents. This leads to demands of unified contents management services. Thus, this paper proposestag clustering method based on semantic similarity for effective image categorization. We calculate the cost of semantic similarity between tags and cluster tags that are closely related. If tags are in a cluster, we suppose that images with them are also in a same cluster. Furthermore, we could recommend tags for new images on the basis of initial clusters.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.317-324
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• 2016

This paper proposes a message transfer application using smartphone with NFC(Near Field Communication) and GCM(Goolge Cloud Messaging) technology for prevention of personal information leakage. In implementing for the proposed system, we design a NFC-based vehicle status alerts service which make it possible to communicate with smartpone message without phone-number between a car driver and an unspecified person. The application provides message communication mechanism without exposing the real phone number, using the NFC tag written with the driver's smartphone device ID and GCM push messages. Through the evaluation result of the actual implemented application, the proposed system can be efficient technology in protection for leakage of personal information such as personal phone- number in daily life.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.47-49
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• 2016

최근 SNS(social networking service)의 사용이 급증함에 따라 SNS에서 발생하는 데이터의 분석이 활발해졌다. 하지만 SNS 데이터는 빠르게 생성되며 정형화 되어 있지 않은 빅데이터이기 때문에 그대로 수집할 경우 분석하기가 어렵다. 본 논문은 분산 스트리밍 처리 기술인 Storm을 사용하여 트위터에서 실시간으로 발생하는 데이터를 수집 및 집계하고, 태그 클라우드를 사용하여 집계 결과를 동적으로 시각화하고자 한다. 또한 사용자가 쉽게 키워드를 입력하고 시각화 결과를 실시간으로 확인할 수 있도록 웹 인터페이스를 구현한다. 그리고 결과를 통해 태그 클라우드의 결과가 시간에 따라 바르게 시각화되었는지 확인한다. 본 논문은 빠르게 발생하는 SNS 데이터로부터 각 키워드와 관련된 정보를 시각화하여 각 사용자에게 제공할 수 있는 우수한 결과가 사료된다.

• The Journal of the Korea Contents Association
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• v.19 no.2
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• pp.1-10
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• 2019

The present research aims to identify the issues that occurred when uploading stock photos to the internet-based stock image agencies and to develop technical solutions based on web service technologies. We identify the issues by examination of previous studies and stock photo uploading systems of major three agencies currently in service. As such, we develop web service technology by focusing on the following matters. First, we apply an automatic tag system to ensure convenience. Second, to ensure safety, we apply a technology that easily enables prevention of portrait rights violations and trademark infringements. We also prepare for measures against possible harmfulness. Third, to ensure completeness, we apply a method which resolves upload failure issues that frequently occurred in the past. In particular, the present research is significant as it applies an automatic image analysis system based on Google Cloud Vision API as the artificial intelligence-based image processing technology. In addition, we develop a web service program which improves user access by using SNS-type screen composition.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.11
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• pp.521-526
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• 2017

Data format of Big data is diverse and vast, and its generation speed is very fast, requiring new management and analysis methods, not traditional data processing methods. Textual mining techniques can be used to extract useful information from unstructured text written in human language in online documents on social networks. Identifying trends in the message of politics, economy, and culture left behind in social media is a factor in understanding what topics they are interested in. In this study, text mining was performed on online news related to a given keyword using topic - oriented analysis technique. We use Latent Dirichiet Allocation (LDA) to extract information from web documents and analyze which subjects are interested in a given keyword, and which topics are related to which core values are related.

• Journal of Information Processing Systems
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• v.5 no.3
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• pp.159-166
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• 2009

As shown in Wikipedia, tagging or cross-linking through major keywords in a document collection improves not only the readability of documents but also responsive and adaptive navigation among related documents. In recent years, the Semantic Web has increased the importance of social tagging as a key feature of the Web 2.0 and, as its crucial phenotype, Tag Cloud has emerged to the public. In this paper we provide an efficient method of automated in-text keyword tagging based on large-scale controlled term collection or keyword dictionary, where the computational complexity of O(mN) - if a pattern matching algorithm is used - can be reduced to O(mlogN) - if an Information Retrieval technique is adopted - while m is the length of target document and N is the total number of candidate terms to be tagged. The result shows that automatic in-text tagging with keywords filtered by Information Retrieval speeds up to about 6 $\sim$ 40 times compared with the fastest pattern matching algorithm.