• 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 KIISE:Software and Applications
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• v.35 no.4
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• pp.219-233
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• 2008

This paper suggests an intelligent semantic blog model to systematically analyze and manage biogosphere with ontology as its conceptual knowledge base. In the model, the system managers may support users to easily find appropriate blog resources by tracking and analyzing various relationships between ontology - they may intelligently recommend Interest blog communities to relevant users by monitoring interaction activities in blogoshpere, dynamically grouping the communities with the ontology. To systematically specify the functionality of our model, 1) we first express the structure of blog resources in terms of objects and relationships between them and then 2) we formalize a set of operators designed to be applied to the resources. System queries are implemented by the combination of the operators.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.937-944
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• 2006

Although people's anxiety about the environmental problem has been getting higher, they are not provided good quality of knowledge about the environment. Based on this situation, Ecoblog can be a new type of online community to educate the public in ecological knowledge. Especially, Ecoblog can be utilized as a method of "preventive education", and it will contribute to reduce great amounts of environmental budget to restore contaminated environment to previous condition. Ecoblog also utilizes the concept of blog which user can create and append their site with chosen themes. A weblog or a blog is a non-commercial webpage regularly updated through the use of a blogging software which allows the user to "publish" kinds of amalgamations of text and graphics to the page as posts. The technology offered in Ecoblog is utilizing the concept of 4D place and game metaphor in order to provide users the sense of participation, interaction and immersion among them and the growing community. Thus, it requires applying the CAAD technology by implementing semantically well-defined building data model as a core database to create a 4D virtual community. This research focuses on defining a 4d spatial framework suitable for developing an online ecological community. Through our study, the state-of-the-art of online community has been studied at the first step. Second, the scenario of using EcoBlog described with content, visualization and navigation are defined based on the critical features derived at the first step. Finally, a 4d spatial framework composed of semantic building data model, content and rule database is constructed to propose factors that are necessary to establish an ecological virtual community. In conclusion, our framework could enhance the comprehension and interaction between users and virtual buildings in the ecological community by integrating the concept of game design, 4D CAD and semantic data model. Such framework can be applied to any online community for an educational purpose.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06a
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• pp.89-90
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• 2007

• Spatial Information Research
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• v.20 no.2
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• pp.129-136
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• 2012

Recently international organizations such as ISO/TC211, OGC, INSPIRE (Infrastructure for Spatial Information in Europe) make an effort to share geospatial data using semantic web technologies. In addition, smart phone and social networking services enable community-based opportunities for participants to share issues of a social phenomenon based on geographic area, and many researchers try to find a method of extracting issues from that. However, serviceable spatial ontologies are still insufficient at application level, and studies of spatial information extraction from SNS were focused on user's location finding or geocoding by text mining. Therefore, a study of extracting spatial phenomenon from social media information and converting it into geosemantic knowledge is very usable. In this paper, we propose a framework for extracting keywords from micro-blog, one of the social media services, finding their relationships using data mining technique, and converting it into spatiotemopral knowledge. The result of this study could be used for implementing a related system as a procedure and ontology model for constructing geoseem antic issue. And from this, it is expected to improve the effectiveness of finding, publishing and analysing spatial issues.

• Journal of Information Technology Services
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• v.15 no.1
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• pp.97-111
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• 2016

In the creative economy paradigm, motivation of the opportunity based startup is a continuous concern to policy-makers. Recently, bigdata anlalytics challenge traditional methods by providing efficient ways to identify social trend and hidden issues in the public sector. In this study the authors introduce a case study using social bigdata analytics for conducting policy analysis. A semantic network analysis was employed using textual data from social media including online news, blog, and private bulletin board which create buzz on the startup business. Results indicates that each media has been forming different discourses regarding government's policy on the startup business. Furthermore, semantic network structures from private bulletin board reveal unexpected social burden that hiders opening a startup, which has not been found in the traditional survey nor experts interview. Based on these results, the authors found the feasibility of using social bigdata analysis for policy-making. Methodological and practical implications are discussed.

• Journal of the Korean Society of Clothing and Textiles
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• v.44 no.2
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• pp.295-309
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• 2020

In 2019, Japan announced trade regulations against Korean products; consequently, the sales of Japanese products in Korea dropped due to a Korean consumers' boycott. This study measured the Korean consumers' political consumption behavior toward Japanese fashion products. Unstructured text data from online media sources and consumer posted sources such as blog and SNS were collected. Text mining techniques and semantic network analysis were used to process unstructured data. This study used text mining techniques and semantic network analysis to process data. The results identified boycotting Japanese fashion products and buycotting alternative products and Korean brands due to consumers' political consumption. Two brand cases were investigated in detail. Online text data before and after the political action were compared and significant changes in consumption as well as emotional expressions were identified. Product related industry sectors were identified in terms of the political consumption of fashion: liquor, automobile and tourism industry sectors were closely linked to the fashion sector in terms of boycotting. More "boycott" and "buycott" fashion brands (reflected in consumer attitudes and feelings) were detected in consumer driven texts than in media driven sources.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.730-739
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• 2010

One of core technology in Web 2.0 is tagging, which is applied to multimedia data such as web document of blog, image and video etc widely. But unlike expectation that the tags will be reused in information retrieval and then maximize the retrieval efficiency, unacceptable retrieval results appear owing to toot limitation of tag. In this paper, in the base of preceding research about image retrieval through tag clustering, we design and implement a topic map generation system which is a semantic knowledge system. Finally, tag information in cluster were generated automatically with topics of topic map. The generated topics of topic map are endowed with mean relationship by use of WordNet. Also the topics are endowed with occurrence information suitable for topic pair, and then a topic map with semantic knowledge system can be generated. As the result, the topic map preposed in this paper can be used in not only user's information retrieval demand with semantic navigation but alse convenient and abundant information service.

• Journal of KIISE
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• v.44 no.11
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• pp.1236-1243
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• 2017

In this paper, we propose a novel way of producing keyword networks, named LSI-based ClusterTextRank, which extracts significant key words from a set of clusters with a mutual information metric, and constructs an association network using latent semantic indexing (LSI). The proposed method reduces the dimension of documents through LSI, decomposes documents into multiple clusters through k-means clustering, and expresses the words within each cluster as a maximal spanning tree graph. The significant key words are identified by evaluating their mutual information within clusters. Then, the method calculates the similarities between the extracted key words using the term-concept matrix, and the results are represented as a keyword association network. To evaluate the performance of the proposed method, we used travel-related blog data and showed that the proposed method outperforms the existing TextRank algorithm by about 14% in terms of accuracy.

• The Journal of Society for e-Business Studies
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• v.12 no.2
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• pp.269-290
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• 2007

RSS is a core component of Web 2.0 which is expected to lead the most important innovation in the new IT environment. In that sense, it is actively utilized to distribute Web contents in various areas such as news, blog, multimedia, medical information, and conference and journal information. Also, it is expected to be a major effective marketing tool in electronic commerce domain. In the paper, we analyzed the problems of current utilization of RSS in domestic shopping malls, and suggest requirements for the effective use of RSS in electronic commerce. Furthermore, we proposed various issues and answers on the implementation of the requirements, and designed the intelligent RSS framework for electronic commerce based on the issues. Syntactic and semantic interoperability between the RSS service provider and the user is one of the most important issues in the framework. We suggested how to implement the interoperability based on Semantic Web technologies.