• Korean Journal of Computational Design and Engineering
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• v.10 no.6
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• pp.402-411
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• 2005

Context-aware engineering services in ubiquitous environments are emerging as a viable alternative to traditional engineering services. Most of the previous approaches are computer-centered rather than human-centered. In this paper, we present a Ubiquitous and Context-Aware computing Framework for collaborative virtual Engineering $(U-CAF\acute{E})$ services. The proposed approach utilizes BPEL-based (Business Process Execution Language) process templates for engineering service orchestration and choreography and adopts semantic web-based context-awareness for providing human-centered engineering services. The paper discusses how to utilize engineering contexts and share this knowledge in support of collaborative virtual engineering services and service interfaces. The paper also discusses how Web services and JINI (Java Intelligent Network Infrastructure) services are utilized to support engineering service federations and seamless Interactions among persons, devices, and various kinds of engineering services.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.184-200
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• 2020

Similarity searching is a basic issue in information processing because of the large size of formal contexts and their complicated derivation operators. Recently, some researchers have focused on knowledge reduction methods by using granular computing. In this process, suitable information granules are vital to characterizing the quantities of attributes and objects. To address this problem, a novel approach to obtain an entropy-weighted concept lattice with inclusion degree and similarity distance (ECLisd) has been proposed. The approach aims to compute the combined weights by merging the inclusion degree and entropy degree between two concepts. In addition, another method is utilized to measure the hierarchical distance by considering the different degrees of importance of each attribute. Finally, the rationality of the ECLisd is validated via a comparative analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3790-3803
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• 2018

Content-based image retrieval is an approach used to query images based on their semantics. Semantic based retrieval has its application in all fields including medicine, space, computing etc. Semantically generated binary hash codes can improve content-based image retrieval. These semantic labels / binary hash codes can be generated from unlabeled data using convolutional autoencoders. Proposed approach uses semi-supervised deep hashing with semantic learning and binary code generation by minimizing the objective function. Convolutional autoencoders are basis to extract semantic features due to its property of image generation from low level semantic representations. These representations of images are more effective than simple feature extraction and can preserve better semantic information. Proposed activation and loss functions helped to minimize classification error and produce better hash codes. Most widely used datasets have been used for verification of this approach that outperforms the existing methods.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.2
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• pp.1-6
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• 2018

The following research questions are examined in this paper. What hinders quality metadata generation and metadata interoperability? What kind of semantic representation technique can be utilized in order to enhance metadata quality and semantic interoperability? This paper suggests a way of handling semantic ambiguity for metadata generation. The conceptual graph is utilized to disambiguate semantic ambiguities caused by isolation of a metadata element and its corresponding definition from the relevant context. The mechanism introduced in this paper has the potential to alleviate issues dealing with inconsistent metadata application and interoperability across digital collections.

• Journal of Internet Computing and Services
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• v.17 no.5
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• pp.9-16
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• 2016

Pervasive computing and Internet of Things (IoT) have recently received considerable interest to deploy solutions for the future Internet. Smart environments are integrated with Semantic Web to provide context-awareness to the processed information. Self-learning techniques have been adopted within smart solutions for efficient retrieval of data but do not process data with privacy parameters for in-place authorization. To overcome this issue, we present a novel approach of deploying access control as a service mechanism within Semantic Web based smart environment by using eXtensible Access Control Markup Language (XACML). The proposed XACML as a Service (XACMLaaS) approach offers fine-grained access control for protecting information within smart environment. In this paper, we have defined mathematical rules for each components of proposed access control service layer. These rules are for implementation of access control using XACML. The proposed approach allows the adaptation of authorization of information at component level and provides scalable solution for authorization policies and rule enforcement within smart environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.3972-3988
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• 2020

Existing methods always rely on statistical features to extract local words for microblog user geolocation. There are many non-local words in extracted words, which makes geolocation accuracy lower. Considering the statistical and semantic features of local words, this paper proposes a microblog user geolocation method by extracting local words based on word clustering and wrapper feature selection. First, ordinary words without positional indications are initially filtered based on statistical features. Second, a word clustering algorithm based on word vectors is proposed. The remaining semantically similar words are clustered together based on the distance of word vectors with semantic meanings. Next, a wrapper feature selection algorithm based on sequential backward subset search is proposed. The cluster subset with the best geolocation effect is selected. Words in selected cluster subset are extracted as local words. Finally, the Naive Bayes classifier is trained based on local words to geolocate the microblog user. The proposed method is validated based on two different types of microblog data - Twitter and Weibo. The results show that the proposed method outperforms existing two typical methods based on statistical features in terms of accuracy, precision, recall, and F1-score.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.476-493
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• 2003

Data broadcast is an effective data transmission method from a data base server to numerous mobile clients due to the restrictions on mobile environment such as low wireless communication bandwidth and energy shortage of mobile devices. There are various broadcast methods based on clients' data access frequencies or semantic relationship of data. The broadcast schedule based only on the access frequencies does not consider semantic relations of data, so that when a client needs to access a series of semantically related data, the client has to listen to the wireless channel for a long time. On the other hand, the broadcast schedule based only on semantic relationship of data makes data access time longer when clients highly request specific data which are not semantically related but frequently accessed. In this paper, we present an efficient data broadcast method based on not only data access frequencies but also semantic relationship to improve mobile clients' query response time. The new hybrid broadcast method we propose creates a data broadcast schedule according to the data access frequencies and then the schedule is adjusted to reflect semantic relationship of data. We show our method is efficient by experimental performance analysis.

• Journal of Information Technology Services
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• v.9 no.3
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• pp.163-178
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• 2010

A service composition has received much interest to provide users with the ad-hoc, seamless, and context-sensitive services dynamically composed from various networked services in context-aware computing environments. In this paper, with the purpose of guiding trends in the researches for dynamic service composition technologies, we investigate and analyze the major related works. For this, we separate semantic based composition from syntax based composition and then establish the comparison criteria by dividing the service composition processes into 3 steps：definition, construction, and execution.

• Journal of Internet Computing and Services
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• v.13 no.1
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• pp.65-74
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• 2012

Cloud services are used for improving business. Moreover, customer relationship management(CRM) approaches use social networking as tools to enhance services to customers. However, most cloud systems do not support the semantic structures, and because of this, vital information from social network sites is still hard to process and use for business strategy. This paper proposes a collaboration framework based on social semantic web for cloud system. The proposed framework consists of components to support social semantic web to provide an efficient collaboration system for cloud consumers and service providers. The knowledge acquisition module extracts rules from data gathered by social agents and these rules are used for collaboration and business strategy. This paper showed the implementations of processing of social network site data in the proposed semantic model and pattern extraction which was used for the virtual grouping of cloud service providers for efficient collaboration.

• Journal of Intelligence and Information Systems
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• v.12 no.2
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• pp.49-65
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• 2006

In this research, we are suggesting intelligent information system fur traveling which is focusing on product bundling and integration of information from various resources on ubiquitous computing environment. It is necessary for products structure to easily integrate according to customers' requirements because traveling product is integrated by various traveling resources like airline, hotel reservation, and so on. To guarantee of traveler's mobility in ubiquitous computing environment, we need product bundling and modification process to configure products and semantic web service which supports ontology based traveling information system to support immediate integrating of traveling information from various resources. In this research, we offer a product bundling and integration of information. It is based on the semantic web service, with several components (single products) to reconfigure a bundle of traveling products.