• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.11
• /
• pp.5323-5343
• /
• 2018

Mobile applications and social networks tend to enhance the need for high-quality content access. To address the rapid growing demand for data services in mobile networks, it is necessary to develop efficient content caching and distribution techniques, aiming at significantly reduction of redundant content transmission and thus improve content delivery efficiency. In this article, we develop optimal cooperative content cache and distribution policy, where a geographical cluster model is designed for content retrieval across the collaborative small cell base stations (SBSs) and replacement of cache framework. Furthermore, we divide the SBS storage space into two equal parts: the first is local, the other is global content cache. We propose an algorithm to minimize the content caching delay, transmission cost and backhaul bottleneck at the edge of networks. Simulation results indicates that the proposed neighbor SBSs cooperative caching scheme brings a substantial improvement regarding content availability and cache storage capacity at the edge of networks in comparison with the current conventional cache placement approaches.

• Journal of Information Science Theory and Practice
• /
• v.10 no.1
• /
• pp.30-44
• /
• 2022

This research aims to identify and reveal the meaning of memes about COVID-19, and explain changes in meme content in regard to the information development of COVID-19 in Indonesia published by the mass media and online media. The data is sourced from memes that are shared on social media, especially WhatsApp groups in the period of January to June 2020. To reveal the meaning of memes, a semiotic analysis of Roland Barthes' model is used. Qualitative analysis is used to reveal the relationship between memes and the information development of COVID-19 in Indonesia. The results of the study show that meme content has shifted according to three stages of information development of COVID-19 in Indonesia published by the mass media and online media. When COVID-19 was not yet confirmed in Indonesia, meme content contained mostly humor that was not educative, moreover it seemed to underestimate the coronavirus. Meme content which is mostly humorous and pornographic occurred when COVID-19 was confirmed in Indonesia and during the lockdown policy. At last, as the government has begun to distribute social assistance, the meme content looks more critical. The results of this research emphasize the urgency of the mass media as a source of public information during the COVID-19 pandemic, become a reference for the community in making memes as a forum for expressing feelings and social criticism, and serve as a reference for the government to act and make the right decisions related to the pandemic that is endemic in their country.

• Journal of Information Science Theory and Practice
• /
• v.5 no.1
• /
• pp.65-84
• /
• 2017

Three most popular information services, Periscope, Ustream, and YouNow, vicarious for all Social Live-Streaming Services (SLSSs), are investigated to analyze their streamers' motivations and the user-generated content. Additionally, we collected demographic data (gender and age). More than 7,500 streams by users from the U.S., Germany, and Japan were observed. Main streamer motivations on SLSSs are boredom, socializing, the need to reach a specific group, the need to communicate, and fun. Important content categories on all three SLSSs are chatting, sharing information, 24/7, and 'slice of life.' We were able to identify differences between users from the U.S., Germany, and Japan as well as between the users of Periscope, Ustream, and YouNow. The main motive to stream in the U.S. is to reach a specific group, while in Japan it is socializing, and in Germany boredom. The top content category for both, YouNow as well as Periscope, is to chat; on Ustream it is 24/7 (i.e., webcams).

• Proceedings of the IEEK Conference
• /
• summer
• /
• pp.395-399
• /
• 2004

We present modality conversion as an effective means for QoS management. We show that modality conversion, in combination with content scaling, would give a wider range of adaptation to support QoS at media level. Here, we consider modality conversion with respect to resource constraint and human factor. To represent modality conversion as well as content scaling, we present the overlapped content value (OCV) model that relates the content value of different modalities with resources. The specification of user preference on modality conversion is divided into qualitative and quantitative levels. The user preference is then integrated into the OCV model so that modality conversion correctly reflects the user's wishes. For the conversion of multiple contents, an optimization problem is formulated and solved by dynamic programming. The experiments show that the proposed approach is efficient to be applied in practice.

• International conference on construction engineering and project management
• /
• 2005.10a
• /
• pp.830-835
• /
• 2005

4D models help construction planners to develop and evaluate construction plans. However, current analyses using 4D models are mainly visual and limit the quantitative comparison of construction alternatives. This paper explores the usefulness of extracting quantitative information from 4D models to support time-space analyses. We use two 4D models of an industry test case to illustrate how to analyze 4D content quantitatively (i.e., work space areas and distances between concurrent activities). This paper shows how these two types of 4D content can be extracted from 4D models to support 4D-based-analysis and novel presentation of construction planning information. We suggest further research to formalize the content of 4D models to enable comparative quantitative analyses of construction planning alternatives. Formalized 4D content will enable the development of reasoning mechanisms that automate 4D-model-based analyses and provide the information content for informative presentations of construction planning information.

• Asia pacific journal of information systems
• /
• v.28 no.3
• /
• pp.183-203
• /
• 2018

In the era of Web 2.0, social media advertising can simultaneously stimulate consumers' brand purchase intention and brand information sharing intention. Product sales and brand information diffusion are equally important for a company that conducts advertising. This study investigates how features of brand content influence social media advertising effectiveness by integrating the stimulus-organism-response model and classic advertising effectiveness models. An analysis of 267 survey questionnaires shows that brand content-related cues, including perceived uniqueness, perceived vividness, and perceived interactivity have significant effects on consumers' affective and cognitive involvement, which then affect their attitude toward brand content. As a result, the consumers' attitude toward the brand and their brand purchase intention, as well as their brand content sharing intention, are positively affected by attitude toward brand content. This study contributes to a better understanding of how social advertising works, which suggests that managers should effectively use social media to conduct advertising.

• ETRI Journal
• /
• v.38 no.1
• /
• pp.174-184
• /
• 2016

Information identification with image data by means of low-level visual features has evolved as a challenging research domain. Conventional text-based mapping of image data has been gradually replaced by content-based techniques of image identification. Feature extraction from image content plays a crucial role in facilitating content-based detection processes. In this paper, the authors have proposed four different techniques for multiview feature extraction from images. The efficiency of extracted feature vectors for content-based image classification and retrieval is evaluated by means of fusion-based and data standardization-based techniques. It is observed that the latter surpasses the former. The proposed methods outclass state-of-the-art techniques for content-based image identification and show an average increase in precision of 17.71% and 22.78% for classification and retrieval, respectively. Three public datasets - Wang; Oliva and Torralba (OT-Scene); and Corel - are used for verification purposes. The research findings are statistically validated by conducting a paired t-test.

• The Journal of the Korea Contents Association
• /
• v.6 no.5
• /
• pp.113-121
• /
• 2006

As Internet evolves, web sites are becoming more and more complex, and it costs a lot of time and money to update web sites. The explosive growth of a large amount of content has resulted in an excessive server load and high network traffic, and thus it decreases the quality of service. In this research, we designed and implemented an integrated content management system which can be constructed and managed the content easily, and which is combined a merchant system with a personal information system based on the distributed content gathering and searching in order to optimize the utilization of the content itself.

• Journal of the Korea Society of Computer and Information
• /
• v.11 no.2 s.40
• /
• pp.263-273
• /
• 2006

The remarkable development of the internet causes us to have too many homepages and content, to be specialized and subdivided, and to need 'CMS'(Content Management System). Currently, CMS have been developed by many solution providers and studied in many ways. However, it is hard to find a system which is able to construct the specified Culture & Tourism content rapidly and managed them efficiently. Step on these requirement, this paper focus on design and implementation of unified CMS based on recursive relation object model which can be satisfied the demand of the usual people's information service of Culture & Tourism and which can be installed and managed the standardized Culture & Tourism content easily.

• Asia pacific journal of information systems
• /
• v.31 no.4
• /
• pp.606-632
• /
• 2021

With many consumers being exposed to news via social media platforms, news organizations are challenged to attract visitors and generate revenue during visits to their websites. They therefore need detailed information on how to write articles and headlines to increase visitors' engagement with the content to drive advertising revenues. For those news organizations whose business model depends mainly on advertisements, rather than subscriptions, it is particularly crucial to understand what makes the website attractive to their visitors, what drives users to stay on the website, and what factors affect a user's exit decision. The current research examines individual news consumers' choices to find patterns of increase or decrease in user engagement relative to a variety of topics, as well as to the mood or tone of the content. Using clickstream data from a major news organization, the authors develop a user-level dynamic model of clickstream behavior that takes into account the content of both headlines and stories that visitors read. The authors find that readers appear to exhibit state dependence in the tone of the articles that they read. They also show how the topics expressed in headlines can affect the amount of content readers consume when visiting the news organization to a much larger degree than the topics expressed in the content of the article. Online publishers can make use of such findings to present visitors with content that is likely to maintain and/or increase their engagement and consequently drive advertising revenue.