• Journal of Digital Contents Society
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• v.15 no.5
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• pp.603-612
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• 2014

To provide efficient and correct search results, ontology which use the structure of information, is considered as a main mechanism in the semantic web. Therefore, recent research in information retrieval and data construction have emphasized the use of ontologies as a data representation and search mechanism. In this paper, we propose a semantic search method using ontology to improve search ability in web environment. Ontology and knowledge base is used to represent semantic meaning of the data and provide related web documents and facts as results. Also, search result ranking mechanism is proposed. The mechanism use cardinality of the keyword in the contents and structural information of ontology. Experimental results with several query processing indicate that different coefficient value in the expression gives different results in sample ontology system and we propose appropriate values of the coefficient.

• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.93-102
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• 2007

Metadata and ontology can be used to retrieve related information through the inference mure accurately and simply on the Semantic Web. RDF and RDF Schema are general languages for representing metadata and ontology. An enormous number of keywords on the Semantic Web are very important to make practical applications of the Semantic Web because most users prefer to search with keywords. In this paper, we consider a resource as a unit of query results. And we classily queries with keyword conditions into three patterns and propose indexing techniques for keyword-search considering both metadata and ontology. Our index maintains resources that contain keywords indirectly using conceptual relationships between resources as well as resources that contain keywords directly. So, if user wants to search resources that contain a certain keyword, all resources are retrieved using our keyword index. We propose a structure of table for storing RDF Schema information that is labeled using some simple methods.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.89-97
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• 2011

In semantic web information system like ontology that access distributed information from network, efficient query processing requires an advanced caching mechanism to reduce the query response time. P2P network system have become an important infra structure in web environment. In P2P network system, when the query is initiated, reducing the demand of data transformation to source peer is important aspect of efficient query processing. Caching of query and query result takes a particular advantage by adding or removing a query term. Many of the answers may already be cached and can be delivered to the user right away. In web environment, semantic caching method has been proposed which manages the cache as a collection of semantic regions. In this paper, we propose the semantic caching technique in cluster environment of peers. Especially, using schema data filtering technique and schema similarity cache replacement method, we enhanced the query processing efficiency.

• Journal of Internet Computing and Services
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• v.20 no.3
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• pp.33-41
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• 2019

In this paper, we propose a method to learn the redesigned class with background and object for semantic segmentation of indoor scene image. Semantic image segmentation is a technique that divides meaningful parts of an image, such as walls and beds, into pixels. Previous work of semantic image segmentation has proposed methods of learning various object classes of images through neural networks, and it has been pointed out that there is insufficient accuracy compared to long learning time. However, in the problem of separating objects and backgrounds, there is no need to learn various object classes. So we concentrate on separating objects and backgrounds, and propose method to learn after class simplification. The accuracy of the proposed learning method is about 5 ~ 12% higher than the existing methods. In addition, the learning time is reduced by about 14 ~ 60 minutes when the class is configured differently In the same environment, and it shows that it is possible to efficiently learn about the problem of separating the object and the background.

• Journal of Intelligence and Information Systems
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• v.13 no.3
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• pp.17-29
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• 2007

Inference engine that performs the brain of software agent in next generation's web with various standards based on standard language of the web, XML has to understand SWRL (Semantic Web Rule Language) that is a language to express the rule in the Semantic Web. In this research, we want to develop a forward inference engine, SMART-F (SeMantic web Agent Reasoning Tools-Forward chaining inference engine) that uses SWRL as a rule express method, and OWL as a fact express method. In the traditional inference field, the Rete algorithm that improves effectiveness of forward rule inference by converting if-then rules to network structure is often used for forward inference. To apply this to the Semantic Web, we analyze the required functions for the SWRL-based forward inference, and design the forward inference algorithm that reflects required functions of next generation's Semantic Web deducted by Rete algorithm. And then, to secure each platform's independence and portability in the ubiquitous environment and overcome the gap of performance, we developed management tool of fact and rule base and forward inference engine. This is compatible with fact and rule base of SMART-B that was developed. So, this maximizes a practical use of knowledge in the next generation's Web environment.

• Journal of Gifted/Talented Education
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• v.25 no.2
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• pp.195-216
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• 2015

Students' perceived values of career play a core role in formation of their career motivation. In particular, science gifted students should build sound values of career in science and technology so that our society can retain the human resources for future science and technology. This study compared and analyzed the structure of science gifted and general middle school students' preferred job and values of career using semantic network analysis. Methodologically, we first collected science gifted and general middle school students' preferred careers and the reasons of the career choice using survey method. Then, we structuralize semantic networks of students' perceived values of their preferred careers using semantic network analysis. We identified the characters of networks that two different student groups showed based on the structure matrix indices of semantic network analysis. Findings revealed that science gifted students considered the creativeness as the most important value of career. Second, science gifted students considered more diverse values of career than general students. Third, science gifted students considered the self-realization such as displaying capability as a core value of career in STEM and medical science whereas general students considered the community service as a core value of the careers. This study identified the significant differences between science gifted and general middle school students' values of careers. The structures of students perceived values of careers can be used for teachers to counsel their students about students' future careers.

• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.76-85
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• 2007

This paper addresses a task of opinion extraction from given documents and its positive/negative classification. We propose a sentence classification method using a notion of syntactic piece. Syntactic piece is a minimum unit of structure, and is used as an alternative processing unit of n-gram and whole tree structure. We compute its semantic orientation, and classify opinion sentences into positive or negative. We have conducted an experiment on more than 5000 opinion sentences of multiple domains, and have proven that our approach attains high performance at 91% precision.

• Journal of Multimedia Information System
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• v.4 no.3
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• pp.123-144
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• 2017

Personalized media includes user-targeted and user-generated content (UGC) exchanged through social media and interactive applications. The increased consumption of UGC presents challenges and opportunities to multimedia information systems. We work towards modeling a deep structure for content networks. To gain insights, a hybrid practice with Media Framework (MF) is presented for network creation of personalized media, which leverages the authoring methodology with user-generated semantics. The system's vertical integration allows users to audition their personalized media networks in the context of a global system network. A navigation scheme with dynamic GUI shifts the interaction paradigm for content query and sharing. MF adopts a multimodal architecture anticipating emerging use cases and genres. To model diversification of platforms, information processing is robust across multiple technology configurations. Physical and virtual networks are integrated with distributed services and transactions, IoT, and semantic networks representing media content. MF applies spatiotemporal and semantic signal processing to differentiate action responsiveness and information responsiveness. The extension of multimedia information processing into authoring enables generating interactive and impermanent media on computationally enabled devices. The outcome of this integrated approach with presented methodologies demonstrates a paradigmatic shift of the concept of UGC as personalized media network, which is dynamical and evolvable.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.1-14
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• 2015

To conform to new emerging computing paradigm, various researches and challenges are being done. New information technologies make easy to access and acquire information in various ways. In other side, however, it also makes illegal access more powerful and various threat to system security. In this paper, we suggest a new extended access control method that make it possible to conform to security policies enforcement even with discrepancy between policy based constraints rules and query based constraints rules, based on their semantic information. New method is to derive security policy rules using context tree structure and to control the exceed granting of privileges through the degree of the semantic discrepancy. In addition, we illustrate prototype system architecture and make performance comparison with existing access control methods.

• Korean Journal of Cognitive Science
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• v.10 no.4
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• pp.1-10
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• 1999

A Semantic Hierarchy of Korean Nouns(SHKN) where Korean nouns are semantically and hierarchically classified is one of the most important things that can provide semantic information concerned with processing the Korean sentences. In this paper. SHKN is constructed in bottom-up method by making use of the definition of a noun in the Korean dictionary. SHKN constructed in this paper is a forest which consist of 43 trees and 2.443 non-terminal nodes and 10.347 terminal nodes. depth of which is 17. The classes of level 1. 2 of SHKN is quite different from the existing structure classified in top-down method. 2 b but the lower classes than level 2 is very objective.