• International Journal of Advanced Culture Technology
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• v.8 no.3
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• pp.223-230
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• 2020

Companies have made an investment of cost and time to optimize processing of a new business model in a cloud environment, applying collaboration technology utilizing business processes in a social network. The collaborative processing method changed from traditional BPM to the cloud and a mobile cloud environment. We proposed a collaborative system for operating processes in social networks using MOXMDR-DAI+ (eXtended Metadata Registry-Data Access & Integration based multimedia ontology). The system operating cloud-based collaborative processes in application of MOXMDR-DAI+, which was suitable for data interoperation. MOXMDR-DAI+ applied to this system was an agent effectively supporting access and integration between multimedia content metadata schema and instance, which were necessary for data interoperation, of individual local system in the cloud environment, operating collaborative processes in the social network. In operating the social network-based collaborative processes, there occurred heterogeneousness such as schema structure and semantic collision due to queries in the processes and unit conversion between instances. It aimed to solve the occurrence of heterogeneousness in the process of metadata mapping using MOXMDR-DAI+ in the system. The system proposed in this study can visualize business processes. And it makes it easier to operate the collaboration process through mobile support. Real-time status monitoring of the operation process is possible through the dashboard, and it is possible to perform a collaborative process through expert search using a community in a social network environment.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.5
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• pp.390-394
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• 2009

The semantic web-based social network is highly useful in a variety of areas. In this paper we make diverse analyses of the FOAF-based social network, and propose an expert recommendation system. This system presents useful method of ontology-based social network using SparQL, RDFS inference, and visualization tools. Then we apply it to real social network in order to make various analyses of centrality, small world, scale free, etc. Moreover, our system suggests method for analysis of an expert on specific field. We expect such method to be utilized in multifarious areas - marketing, group administration, knowledge management system, and so on.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1168-1188
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• 2018

Social Network Aggregators are used to maintain and manage manifold accounts over multiple online social networks. Displaying the Activity feed for each social network on a common dashboard has been the status quo of social aggregators for long, however retrieving the desired data from various social networks is a major concern. A user inputs the query desiring the specific outcome from the social networks. Since the intention of the query is solely known by user, therefore the output of the query may not be as per user's expectation unless the system considers 'user-centric' factors. Moreover, the quality of solution depends on these user-centric factors, the user inclination and the nature of the network as well. Thus, there is a need for a system that understands the user's intent serving structured objects. Further, choosing the best execution and optimal ranking functions is also a high priority concern. The current work finds motivation from the above requirements and thus proposes the design of a query processing system to retrieve information from social network that extracts user's intent from various social networks. For further improvements in the research the machine learning techniques are incorporated such as Latent Dirichlet Algorithm (LDA) and Ranking Algorithm to improve the query results and fetch the information using data mining techniques.The proposed framework uniquely contributes a user-centric query retrieval model based on natural language and it is worth mentioning that the proposed framework is efficient when compared on temporal metrics. The proposed Query Processing System to Retrieve Information from Social Network (QPSSN) will increase the discoverability of the user, helps the businesses to collaboratively execute promotions, determine new networks and people. It is an innovative approach to investigate the new aspects of social network. The proposed model offers a significant breakthrough scoring up to precision and recall respectively.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.903-905
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• 2012

Recent research on Augmented Reality is Actively expand and Augmented reality feature added to the social network system (Social Network System) has become a necessity. In this paper, GPS-based Augmented Reality System for Social Network is introduced, is proposed. This system can add recent check-in friends in facebook by automatically to synchronizing the location coordinate, and it could also adding location coordinates system is represented in a real-world environment by AR, is Marker-based AR system that was Commonly used AR system is a huge cost by handheld devices in processing and storage space, the disadvantages of the marker-based AR systems can be solved by using Location-based AR applications. Therefore, the proposed GPS-based Augmented Reality System for Social Network, automatically searches for the optimal speed for Wifi and 4G network to iOS Hand AR system was desired in future.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.1
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• pp.43-52
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• 2013

Pervasive computing and social network are good resources in recommendation method. Collaborative filtering is one of the most popular recommendation methods, but it has some limitations such as rating sparsity. Moreover, it does not consider social network in pervasive computing environment. We propose an effective proactive friend recommendation method using social network and contexts in pervasive computing environment. In collaborative filtering method, users need to rate sufficient number of items. However, many users don't rate items sufficiently, because the rating information must be manually input into system. We solve the rating sparsity problem in the collaboration filtering method by using contexts. Our method considers both a static and a dynamic friendship using contexts and social network. It makes more effective recommendation. This paper describes a new friend recommendation method and then presents a music friend scenario. Our work will help e-commerce recommendation system using collaborative filtering and friend recommendation applications in social network services.

• International journal of advanced smart convergence
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• v.6 no.2
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• pp.34-50
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• 2017

This study delved into the effects of labor union members' social media utilization for the formation of labor union social capital. Specifically, this study aimed to identify the effects of labor union-related social media use and participation on the labor union's social capital formation through quantitative and qualitative research. It set up trust, network, and participation as social capital components and as dependent variables. Network, in particular, was divided into bonding and bridging aspect. There is the correlation between labor union-related social media use and the formation of labor union social capital. As participation in the group type social media operated by a labor union becomes more active, evaluation on labor union social capital throughout trust, network, and participation is higher. Especially, the correlation between bonding network and bridging network was high. This proves that a labor union's bond enhancement does not result in the labor union's selfishness, but it can build a cooperative system with an external network.

• Journal of Internet Computing and Services
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• v.14 no.2
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• pp.35-43
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• 2013

As the number of podcast users consistently increases which is rising as a new media along with the generalization of SNS and smart devices, the necessity for advanced search service is on the rise. This study designed and implemented a system which recommends a podcast to the users who search podcast by using their social network information. Suggested social network-based podcast search system (PODSSO) collects necessary podcast information only, analyzes social network of the users and makes the users have reliable and interested podcast search results.

• Journal of Distribution Research
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• v.16 no.2
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• pp.95-118
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• 2011

The purpose of this study is as follows. First, we investigate empirically the effects of social network properties such as social network density and centrality of a franchisee on its information sharing with various subjects such as the franchisor and other franchisees in the franchise system. Second, we examine exploratively if tie strength between a franchisee and its franchisor plays a moderating role on the relationship between social network properties and information sharing. The study model was established as shown in

• Journal of Information Management
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• v.40 no.1
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• pp.199-215
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• 2009

The web 2.0 concept rapidly spreads to the various field which is based on an opening, the participation, and a share. And the research about the recommendation system, that is the personalize feature, and social network is very active. In the case of the recommendation system and social network, it had been developing in the respectively different area and the new research toward the service model of a form that it fuses these is insignificant. In this paper, I'm going to introduce efficient social network which is called the researcher connection network. It is possible to recommend the researcher intellectually who studies the similar field by analyzing the usage log and user profile. Through this study, we could solved the network expandability problem which is due to the user passive participation and the difficulty of the initial network construction that is the conventional social network problem.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.3
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• pp.762-767
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• 2013

Recently, researches on augmented reality(AR) are actively being conducted, and on addition of AR in social network system has become a necessity. In this paper, we propose GPS-based AR system for social network. This proposed system adds the recent check-in coordinates by automatically synchronizing a friend list in facebook and represents those added location coordinates in a real-world environment by using AR. Marker-based AR system that was commonly used by existing users consumes too much storage space and processing frequency for driving handle devices. But, location-based AR application can solves the disvantages of the standard marker=based AR system. Therefore, this proposed system allows an user with iOS hand devices to use GPS-based AR system by automatically searching the optimal speed for wifi and 4G. This will improve social network service.