• Asia pacific journal of information systems
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• v.18 no.1
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• pp.117-144
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• 2008

Lots of virtual communities and online businesses presently derive their primary sources of revenues through advertising, but nevertheless are plagued with marginal profitability though they might possess a significant user base. In the light of the need for an efficacious business model, there have been recent insights of an online community in particular reaping profits through an innovative and lucrative revenue generation method that earns by selling digital items. There have been some obvious evidences (e.g., Cyworld, SecondLife, Habo Hotel, etc.) that online communities can be profitable through their unique business model of selling digital items. However, there is lack of understanding about the motivation of purchasing digital items. This study tries to identify the main motivators of digital item purchases based on social/individual identity theory and self-presentation theory. "Digital items", otherwise known as "virtual assets", may include online avatars, accessories for the avatars, decorative ornaments like furniture, digital wallpapers, skins, background music and virtual weapons used for Internet games. These digital items are employed by users for representation and articulation in the online space, especially to create and enhance their online profiles in web pages and games. Prices for digital items typically range from a few cents to a few dollars each. Based on the theoretical framework like social identity theory and self-presentation theory, we developed the research model and proposed seven hypotheses. An analysis of 225 members of Cyworld found that digital item purchase intention in virtual world is affected by both members' need for self-presentation and need for affiliation. We also found that the need for self-presentation is significantly increased by innovativeness of members, community group norm, and community involvement. We concluded that the need for self-presentation could be a key variable for profitable business model in online community service industry. However, neither individual self-efficacy nor the need for affiliation significantly influenced the need for self-presentation which triggers purchase intention of digital items. In term of the theoretical and practical contribution, this study can be a pioneering empirical research that investigates the purchase intention of digital items based on social identity theory and self-presentation theory in the online context. Also, the findings of our study are valuable and practical for practitioners in the market who wish to adopt or improve the business model of selling digital items in an online community. From the findings, it can be seen that innovativeness of users, community group norm, and community involvement are three significant factors that influence need for self-presentation of users which ultimately leads to their intentions to buy digital items. These findings put forth that virtual community providers and online businesses selling digital items should prioritize their efforts and focus on these three factors if they want to increase the sales of these digital items and generate greater revenues. This study provides important implications for academic researchers and practitioners to understand why the community members pay money for their digital items in virtual world and how the practitioners can increase the sales of digital items in an online community. A couple of limitations of the study and future research directions are also discussed.

• Korean Journal of Social Welfare
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• v.66 no.4
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• pp.181-205
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• 2014

The purpose of this study is to analyze the process of growth of parental empowerment of the family of the children with development disabilities in an online parental community. For this purpose, 250 posts were selected from a web-forum of an online-community(internet CAFE) for patients with developmental disabilities in a Korean portal site. In addition, the selected posts were analyzed based on the grounded theory method. The results showed that the parents with high risk children for developmental disabilities interacted with each other in short answers, self-addressing, and discussion type interactions under the causal condition in which the subject parents were in need of help and sympathy. The factors that significantly affected the focus event, which is the interactive communication between the posters of the original threads and replies, included the moderating conditions based on whether the conversation was respectful, friendly, or for general evaluation, as well as the contextual condition of exclusive attitudes. The strategies of the interactions were composed of two categories of self-reflections and sharing through a human relationship. The results of these interactions were either further interactions (sharing) or shying away. With regard to the process of reinforcing the collective empowerment of the family, the 'determination,' 'tips,' and 'empathy' models were used for the explanation of the process. Lastly, we discovered that trust, support, continuous interactions, specific and practical information, as well as provision of diversified perspectives through collective experiences are necessary to achieve such improvement of collective family empowerment.

• The Journal of the Korea Contents Association
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• v.9 no.9
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• pp.18-30
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• 2009

Recently, although the requirement of quality of VOD content has been transferred upto the class of HD, conventional management systems characterized by OS dependency are truly limited in quality of video image, stability, and compatibility of network environments. In addition most of the content management systems realize very limited capabilities for the real affairs of content management and distribution services in such an OS dependent environment. In this paper, we propose a new scheme of HD-Class VOD Content Management System to solve these problems. We design and implement the proposed system based on open sources by using H.264 video compression method. The proposed system offers high quality content management method based on opened systems and independent on-line distribution method so that it can be realized as an integrated management scheme for VOD contents. Moreover, our system solves the problems of occasional cutting-down video, small screen, and poor image quality that exist in the conventional wmv-type CMS. According to the result of performance evaluation, our system maintains sufficient performance and tolerence for the case of large scale HD content operations or fabrications. We expect that the proposed integrated DB scheme will especially be effective when the content management applications are changed from Internet Web environments to mobile terminal environments.

• The Journal of Korean society of community based occupational therapy
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• v.8 no.3
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• pp.13-23
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• 2018

Objective : This study was conducted to investigate the leisure activities and self-efficacy according to sensory processing feature of university students. Methods : The survey was conducted from March to June, 2018. A total of 235 university students in Jeolla and Gyeongsang area participated. We used Adolescent/Adult Sensory Profiles to investigate sensory processing feature, Leisure Activity Questionnaires to examine leisure activities, and Self-Efficacy Scale for self-efficacy. This study identified the frequency of leisure activities of university students, the frequency of leisure activities and self-efficiency according to the sensory processing feature, and the leisure activities according to the feature of sensory seeking. Results : For the frequency of leisure activities and self-efficacy according to sensory processing feature of university students, only sensory seeking showed significantly difference in the leisure activity frequency, and the self-efficacy was significantly difference according to the feature of all types of sensory processing (p<.05). In addition, this study identified that leisure activities according to the feature of sensory seeking showed a significantly difference in gym, watching TV, shopping, internet search and web surfing (p<.05, p<.01). Conclusion : According to sensory seeking feature of university students, leisure activities and self-efficacy showed a significant difference. In order to encourage leisure activities of university students and to improve their self-efficacy, an interventional approach based on an understanding of sensory processing characteristics will be needed.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.145-154
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• 2022

Automatic Target Recognition (ATR) technology is emerging as a core technology of Future Combat Systems (FCS). Conventional ATR is performed based on IMINT (image information) collected from the SAR sensor, and various image-based deep learning models are used. However, with the development of IT and sensing technology, even though data/information related to ATR is expanding to HUMINT (human information) and SIGINT (signal information), ATR still contains image oriented IMINT data only is being used. In complex and diversified battlefield situations, it is difficult to guarantee high-level ATR accuracy and generalization performance with image data alone. Therefore, we propose a knowledge graph-based ATR method that can utilize image and text data simultaneously in this paper. The main idea of the knowledge graph and deep model-based ATR method is to convert the ATR image and text into graphs according to the characteristics of each data, align it to the knowledge graph, and connect the heterogeneous ATR data through the knowledge graph. In order to convert the ATR image into a graph, an object-tag graph consisting of object tags as nodes is generated from the image by using the pre-trained image object recognition model and the vocabulary of the knowledge graph. On the other hand, the ATR text uses the pre-trained language model, TF-IDF, co-occurrence word graph, and the vocabulary of knowledge graph to generate a word graph composed of nodes with key vocabulary for the ATR. The generated two types of graphs are connected to the knowledge graph using the entity alignment model for improvement of the ATR performance from images and texts. To prove the superiority of the proposed method, 227 documents from web documents and 61,714 RDF triples from dbpedia were collected, and comparison experiments were performed on precision, recall, and f1-score in a perspective of the entity alignment..

• Journal of Internet Computing and Services
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• v.15 no.4
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• pp.91-102
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• 2014

The purpose of this research is to perform the consumer typological study of integrated emerging digital advertisement, where IT and advertisement industry were fused, and to propose the theoretical definition about consumer characteristic which is in need for collection of related market subdivision strategy in perspective of business marketing. For this, the Q methodology, the 'subjectivity' research of qualitative perspective, which discovers new theory by interpreting subjective system of thinking, preference, opinion, and recognition of inner side of respondents, was applied and analyzed. Compared to previous quantitative research that pursues hypothesis verification, this Q methodology is not dependent on operational definition proposed by researcher but pursues for analytic study completely reflecting objective testimony of respondents. For this reason, Q study analyzes in-depth the actual consumer type, which can be found at the initial market formation stage of new service, therefore this study is applicable for theorizing the consumer character as a mean of advanced research. This study extracted thirty 'IT integrated digital advertisement type (Q sample)' from thorough literature research and interviews, and eventually discovered a total four consumer types from analyzing each Q sorting research data of 40 respondents (P sample). Moreover, by interpreting subdivided intrinsic characteristic of each group, the four types were named as 'multi-channel digital advertisement pursuit type', 'emotional advertisement pursuit type', 'new media advertisement pursuit type', and Web 2.0 advertisement pursuit type'. The analysis result of this study is being expected for its value of usage as advanced research of academic and industrial research with the emerging digital advertisement industry as a subject, and as basic research in the field of R&D, Marketing program and the field of designing the advertisement creative strategy and related policy.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.4
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• pp.412-429
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• 2008

As the amount of electronic documents increases rapidly with the growth of the Internet, a parallel search engine capable of handling a large number of documents are becoming ever important. To implement a parallel search engine, we need to partition the inverted index and search through the partitioned index in parallel. There are two methods of partitioning the inverted index: 1) document-identifier based partitioning and 2) keyword-identifier based partitioning. However, each method alone has the following drawbacks. The former is convenient in inserting documents and has high throughput, but has poor performance for top h query processing. The latter has good performance for top-k query processing, but is inconvenient in inserting documents and has low throughput. In this paper, we propose a hybrid partitioning method to compensate for the drawback of each method. We design and implement a parallel search engine that supports the hybrid partitioning method using the Odysseus DBMS tightly coupled with information retrieval capability. We first introduce the architecture of the parallel search engine-Odysseus/parallel-OOSQL. We then show the effectiveness of the proposed system through systematic experiments. The experimental results show that the query processing time of the document-identifier based partitioning method is approximately inversely proportional to the number of blocks in the partition of the inverted index. The results also show that the keyword-identifier based partitioning method has good performance in top-k query processing. The proposed parallel search engine can be optimized for performance by customizing the methods of partitioning the inverted index according to the application environment. The Odysseus/parallel OOSQL parallel search engine is capable of indexing, storing, and querying 100 million web documents per node or tens of billions of web documents for the entire system.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.93-107
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• 2014

In this paper, we report what we have observed with regard to user-perspective issue clustering based on multi-layered two-mode network analysis. This work is significant in the context of data collection by companies about customer needs. Most companies have failed to uncover such needs for products or services properly in terms of demographic data such as age, income levels, and purchase history. Because of excessive reliance on limited internal data, most recommendation systems do not provide decision makers with appropriate business information for current business circumstances. However, part of the problem is the increasing regulation of personal data gathering and privacy. This makes demographic or transaction data collection more difficult, and is a significant hurdle for traditional recommendation approaches because these systems demand a great deal of personal data or transaction logs. Our motivation for presenting this paper to academia is our strong belief, and evidence, that most customers' requirements for products can be effectively and efficiently analyzed from unstructured textual data such as Internet news text. In order to derive users' requirements from textual data obtained online, the proposed approach in this paper attempts to construct double two-mode networks, such as a user-news network and news-issue network, and to integrate these into one quasi-network as the input for issue clustering. One of the contributions of this research is the development of a methodology utilizing enormous amounts of unstructured textual data for user-oriented issue clustering by leveraging existing text mining and social network analysis. In order to build multi-layered two-mode networks of news logs, we need some tools such as text mining and topic analysis. We used not only SAS Enterprise Miner 12.1, which provides a text miner module and cluster module for textual data analysis, but also NetMiner 4 for network visualization and analysis. Our approach for user-perspective issue clustering is composed of six main phases: crawling, topic analysis, access pattern analysis, network merging, network conversion, and clustering. In the first phase, we collect visit logs for news sites by crawler. After gathering unstructured news article data, the topic analysis phase extracts issues from each news article in order to build an article-news network. For simplicity, 100 topics are extracted from 13,652 articles. In the third phase, a user-article network is constructed with access patterns derived from web transaction logs. The double two-mode networks are then merged into a quasi-network of user-issue. Finally, in the user-oriented issue-clustering phase, we classify issues through structural equivalence, and compare these with the clustering results from statistical tools and network analysis. An experiment with a large dataset was performed to build a multi-layer two-mode network. After that, we compared the results of issue clustering from SAS with that of network analysis. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The sample dataset contains 150 million transaction logs and 13,652 news articles of 5,000 panels over one year. User-article and article-issue networks are constructed and merged into a user-issue quasi-network using Netminer. Our issue-clustering results applied the Partitioning Around Medoids (PAM) algorithm and Multidimensional Scaling (MDS), and are consistent with the results from SAS clustering. In spite of extensive efforts to provide user information with recommendation systems, most projects are successful only when companies have sufficient data about users and transactions. Our proposed methodology, user-perspective issue clustering, can provide practical support to decision-making in companies because it enhances user-related data from unstructured textual data. To overcome the problem of insufficient data from traditional approaches, our methodology infers customers' real interests by utilizing web transaction logs. In addition, we suggest topic analysis and issue clustering as a practical means of issue identification.

• Journal of Information Management
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• v.37 no.1
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• pp.83-103
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• 2006

This study analyzes the classification schemes and classified information resources of the directory services provided by major web portals to complement keyword-based retrieval. Specifically, this study intends to quantitatively analyze the topic categories, the information resources by subject, and the information resources classified by the topic categories of three directories, Yahoo, Naver, and Empas. The result of this analysis reveals some differences among directory services. Overall, these directories show different ratios of referred categories to original categories depending on the subject area, and the categories regarded as format-based show the highest proportion of referred categories. In terms of the total amount of classified information resources, Yahoo has the largest number of resources. The directories compared have different amounts of resources depending on the subject area. The quantitative analysis of resources classified by the specific category is performed on the class of 'News & Media'. The result reveals that Naver and Empas contain overly specified categories compared to Yahoo, as far as the number of information resources categorized is concerned. Comparing the depth of the categories assigned by the three directories to the same information resources, it is found that, on average, Yahoo assigns one-step further segmented divisions than the other two directories to the identical resources.

• The Journal of the Korea Contents Association
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• v.12 no.4
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• pp.198-215
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• 2012

Green Exhibition and Convention property of the participant satisfaction and impact on the performance of participating companies by looking out for the future development of the national economy on the local economy and help the continued growth of the Green Exhibition and Convention that will help to provide basic data for the purpose of. The results of this study participated in the Green Exhibition and Convention on the expectation of fame exhibit variable, based on the venue, the exhibition publicity, Green Exhibition and Convention Services, Green Exhibition and Convention facilities, information, PC communication or the Internet web site, information, and with the encouragement of those around these parameters and variables of trust as being based on the venue, the exhibition publicity, Green exhibition and Convention Services, Convention and Exhibition as being green in order to increase its influence on expectations and confidence to increase the satisfaction of the variable parameters should be of the utmost importance. Participants to meet the expectations of the variables in the Exhibition, Exhibition of trust, sex, male and recommendation showed by influence. This is an important variable affecting showed. Satisfaction of participants and exhibitors were on.