• Journal of KIISE:Computing Practices and Letters
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• v.15 no.6
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• pp.405-413
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• 2009

Tagging system is the system that allows internet users to assign new meta-data which is called tag to article, photo, video and etc. for facilitating searching and browsing of web contents. Tag cloud, a visual interface is widely used for browsing tag space. Tag cloud selects the tags with the highest frequency and presents them alphabetically with font size reflecting their popularity. However the conventional tag selection method includes known weaknesses. So, we propose a novel tag selection method Freshness, which helps to find fresh web contents. Freshness is the mean value of Kullback-Leibler divergences between each consecutive change of tag co-occurrence probability distribution. We collected tag data from three web sites, Allblog, Eolin and Technorati and constructed the system, 'Fresh Tag Cloud' which collects tag data and creates our tag cloud. Comparing the experimental results between Fresh Tag Cloud and the conventional one with data from Allblog, our one shows 87.5% less overlapping average, which means Fresh Tag Cloud outperforms the conventional tag cloud.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.589-592
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• 2007

웹사이트의 블로그에서 등록된 게시물을 분류, 표현하는 방식으로 카테고리 분류방식과 Tag cloud 분류방식을 사용하고 있다. 그러나 카테고리분류방식은 같은 게시물이라도 블로그 관리자별로 해당 분류의 생성기준이 주관적인 판단에 따라 다른 분류에 속할 수 있어 이용자들이 찾고자 하는 게시물을 검색하는데 많은 시간이 소요될 수 있다는 단점이 있다. 또한 이를 보완하는 방안으로 사용되는 Tag cloud 방식은 태그들을 흩어놓아 원하는 정보를 빠르게 찾는데 한계가 있다. 이에 본 논문은 블로그에서 태그들을 그룹화하여 구현한 트리형 Tag cloud(이하 'TreeTag cloud') 모델을 통해 카테고리 분류방식의 트리 구조의 장점인 직관성 및 구조화와 Tag cloud 분류방식의 장점인 짧은 search depth 를 결합하여 구현하는 방법을 제안하였다.

• Journal of KIISE
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• v.42 no.5
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• pp.637-641
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• 2015

Due to the recent increasement of user created contents like SNS, blog posts, and so on, broadcast contents are actively re-construction by its users. Especially, on some genres like drama, movie, various information from cars and film sites to clothes and watches in a content is spreaded out to other users through blog postings. Since such information can be an additional information for the content, they can be used for providing high-quality broadcast services. For this purpose, in this paper, we propose timeline tag cloud generation method for broadcasting contents. In the proposed method, blog postings on the target contents are first gathered and then, images and words around images are extracted from a blog post as a tag set. An extracted tag set is tagged on a specific timeline of the target content. In experiments, to prove the efficiency of the proposed method, we evaluated the performances of the proposed image matching and tag cloud generation methods.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.6
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• pp.309-314
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• 2017

In general, there are many difficulties in collecting, storing, and analyzing SNS (social network service) data, since those data have big data characteristics, which occurs very fast with the mixture form of structured and unstructured data. In this paper, we propose a new data visualization framework that works on Apache Storm, and it can be useful for real-time and dynamic analysis of SNS data. Apache Storm is a representative big data software platform that processes and analyzes real-time streaming data in the distributed environment. Using Storm, in this paper we collect and aggregate the real-time Twitter data and dynamically visualize the aggregated results through the tag cloud. In addition to Storm-based collection and aggregation functionalities, we also design and implement a Web interface that a user gives his/her interesting keywords and confirms the visualization result of tag cloud related to the given keywords. We finally empirically show that this study makes users be able to intuitively figure out the change of the interested subject on SNS data and the visualized results be applied to many other services such as thematic trend analysis, product recommendation, and customer needs identification.

• Journal of Korea Multimedia Society
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• v.20 no.12
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• pp.1928-1939
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• 2017

Fog computing is another paradigm of the cloud computing, which extends the ubiquitous services to applications on many connected devices in the IoT (Internet of Things). In general, if we access a lot of IoT devices with existing cloud, we waste a huge amount of bandwidth and work efficiency becomes low. So we apply the paradigm called fog between IoT devices and cloud. The network architecture based on cloud and fog computing discloses the security and privacy issues according to mixed paradigm. There are so many security issues in many aspects. Moreover many IoT devices are connected at fog and they generate much data, therefore light and efficient security mechanism is needed. For example, with inappropriate encryption or authentication algorithm, it causes a huge bandwidth loss. In this paper, we consider issues related with data encryption and authentication mechanism in the network architecture for cloud and fog-based M2M (Machine to Machine) IoT services. This includes trusted encryption and authentication algorithm, and key generation method. The contribution of this paper is to provide efficient security mechanisms for the proposed service architecture. We implemented the envisaged conceptual security check mechanisms and verified their performance.

• Journal of the Korean Society for Library and Information Science
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• v.50 no.2
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• pp.183-196
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• 2016

The academic journal is an important medium carrying newly discovered knowledge in various disciplines. It is desirable to consider visualization of journal and article information in order to make the information more insightful and effective than text-based information. In this study, visualization service platform of journal and article information is developed. TagCloud were included in both Infographics of journal and article. Each word in the TagCloud is inter-linked with DBPedia using Linked Open Data (LOD) technique.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.2219-2236
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• 2017

With cloud storage services, users can handle an enormous amount of data in an efficient manner. However, due to the widespread popularization of cloud storage, users have raised concerns about the integrity of outsourced data, since they no longer possess the data locally. To address these concerns, many auditing schemes have been proposed that allow users to check the integrity of their outsourced data without retrieving it in full. Yuan and Yu proposed a public auditing scheme with a deduplication property where the cloud server does not store the duplicated data between users. In this paper, we analyze the weakness of the Yuan and Yu's scheme as well as present modifications which could improve the security of the scheme. We also define two types of adversaries and prove that our proposed scheme is secure against these adversaries under formal security models.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.525-528
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• 2007

기존의 웹서비스가 정적이고 수동적인데 반해 최근의 웹 서비스는 점차 동적이고 능동적으로 변화하고 있다. 이러한 웹서비스 변화의 흐름을 잘 반영하는 것이 웹 2.0이다. 웹 2.0에서 대부분의 정보는 사용자에 의해 생산되고, 사용자가 붙인 태그(tag)에 의해 분류되어진다. 그러나 현재 태그에 관한 서비스 및 연구들은 태깅(tagging) 방법에 대한 연구를 비롯해 이를 표현하기 위한 tag cloud에 초점이 맞춰져 진행됨에 따라, 다양한 태그 정보자원 간의 체계와 연결 관계인 지식체계를 제공하지 못하고 있다. 이에 본 논문에서는 체계화된 지식표현을 위해 웹상에 편재되어 있는 학습 관련 리소스(resources) 및 태그들를 수집한다. 이를 사용자가 요청한 검색 키워드와 연관성이 있는 태그 정보들을 맵핑 및 클러스터링하여 최적화된 표현 형식인 토픽 맵(topic map)화하기 위한 시스템을 제안하며, 이 중 토픽 맵 생성을 위한 초기 연구 단계로서, 연관 태그들 간의 맵핑 및 클러스터링을 위한 알고리즘 제시를 중심으로 소개한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4576-4598
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• 2018

In big data age, flexible and affordable cloud storage service greatly enhances productivity for enterprises and individuals, but spontaneously has their outsourced data susceptible to integrity breaches. Provable Data Possession (PDP) as a critical technology, could enable data owners to efficiently verify cloud data integrity, without downloading entire copy. To address challenging integrity problem on multiple clouds for multiple owners, an identity-based batch PDP scheme was presented in ProvSec 2016, which attempted to eliminate public key certificate management issue and reduce computation overheads in a secure and batch method. In this paper, we firstly demonstrate this scheme is insecure so that any clouds who have outsourced data deleted or modified, could efficiently pass integrity verification, simply by utilizing two arbitrary block-tag pairs of one data owner. Specifically, malicious clouds are able to fabricate integrity proofs by 1) universally forging valid tags and 2) recovering data owners' private keys. Secondly, to enhance the security, we propose an improved scheme to withstand these attacks, and prove its security with CDH assumption under random oracle model. Finally, based on simulations and overheads analysis, our batch scheme demonstrates better efficiency compared to an identity based multi-cloud PDP with single owner effort.

• Journal of Korea Multimedia Society
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• v.11 no.8
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• pp.1169-1178
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• 2008

Most of information in Web2.0 is constructed by users and can be classified by tags which are also constructed and added by users. However, as we known, referring by the related works such as automatic tagging techniques and tag cloud's construction techniques, the research to be classified information and resources by tags effectively is to be given users which is still up to the mark. In this paper, we propose and implement a clustering system that does mapping each other according to relationships of the resource's tags collected from Web and then makes the mapping result into clusters to retrieve images. Tn addition, we analyze our system's efficiency by comparing our proposed system's image retrieval result with the image retrieval results searched by Flickr website.