• Asia pacific journal of information systems
• /
• v.17 no.4
• /
• pp.31-59
• /
• 2007

We frequently use search engines to find relevant information in the Web but still end up with too much information. In order to solve this problem of information overload, ranking algorithms have been applied to various domains. As more information will be available in the future, effectively and efficiently ranking search results will become more critical. In this paper, we propose a ranking algorithm for the Semantic Web resources, specifically RDF resources. Traditionally, the importance of a particular Web page is estimated based on the number of key words found in the page, which is subject to manipulation. In contrast, link analysis methods such as Google's PageRank capitalize on the information which is inherent in the link structure of the Web graph. PageRank considers a certain page highly important if it is referred to by many other pages. The degree of the importance also increases if the importance of the referring pages is high. Kleinberg's algorithm is another link-structure based ranking algorithm for Web pages. Unlike PageRank, Kleinberg's algorithm utilizes two kinds of scores: the authority score and the hub score. If a page has a high authority score, it is an authority on a given topic and many pages refer to it. A page with a high hub score links to many authoritative pages. As mentioned above, the link-structure based ranking method has been playing an essential role in World Wide Web(WWW), and nowadays, many people recognize the effectiveness and efficiency of it. On the other hand, as Resource Description Framework(RDF) data model forms the foundation of the Semantic Web, any information in the Semantic Web can be expressed with RDF graph, making the ranking algorithm for RDF knowledge bases greatly important. The RDF graph consists of nodes and directional links similar to the Web graph. As a result, the link-structure based ranking method seems to be highly applicable to ranking the Semantic Web resources. However, the information space of the Semantic Web is more complex than that of WWW. For instance, WWW can be considered as one huge class, i.e., a collection of Web pages, which has only a recursive property, i.e., a 'refers to' property corresponding to the hyperlinks. However, the Semantic Web encompasses various kinds of classes and properties, and consequently, ranking methods used in WWW should be modified to reflect the complexity of the information space in the Semantic Web. Previous research addressed the ranking problem of query results retrieved from RDF knowledge bases. Mukherjea and Bamba modified Kleinberg's algorithm in order to apply their algorithm to rank the Semantic Web resources. They defined the objectivity score and the subjectivity score of a resource, which correspond to the authority score and the hub score of Kleinberg's, respectively. They concentrated on the diversity of properties and introduced property weights to control the influence of a resource on another resource depending on the characteristic of the property linking the two resources. A node with a high objectivity score becomes the object of many RDF triples, and a node with a high subjectivity score becomes the subject of many RDF triples. They developed several kinds of Semantic Web systems in order to validate their technique and showed some experimental results verifying the applicability of their method to the Semantic Web. Despite their efforts, however, there remained some limitations which they reported in their paper. First, their algorithm is useful only when a Semantic Web system represents most of the knowledge pertaining to a certain domain. In other words, the ratio of links to nodes should be high, or overall resources should be described in detail, to a certain degree for their algorithm to properly work. Second, a Tightly-Knit Community(TKC) effect, the phenomenon that pages which are less important but yet densely connected have higher scores than the ones that are more important but sparsely connected, remains as problematic. Third, a resource may have a high score, not because it is actually important, but simply because it is very common and as a consequence it has many links pointing to it. In this paper, we examine such ranking problems from a novel perspective and propose a new algorithm which can solve the problems under the previous studies. Our proposed method is based on a class-oriented approach. In contrast to the predicate-oriented approach entertained by the previous research, a user, under our approach, determines the weights of a property by comparing its relative significance to the other properties when evaluating the importance of resources in a specific class. This approach stems from the idea that most queries are supposed to find resources belonging to the same class in the Semantic Web, which consists of many heterogeneous classes in RDF Schema. This approach closely reflects the way that people, in the real world, evaluate something, and will turn out to be superior to the predicate-oriented approach for the Semantic Web. Our proposed algorithm can resolve the TKC(Tightly Knit Community) effect, and further can shed lights on other limitations posed by the previous research. In addition, we propose two ways to incorporate data-type properties which have not been employed even in the case when they have some significance on the resource importance. We designed an experiment to show the effectiveness of our proposed algorithm and the validity of ranking results, which was not tried ever in previous research. We also conducted a comprehensive mathematical analysis, which was overlooked in previous research. The mathematical analysis enabled us to simplify the calculation procedure. Finally, we summarize our experimental results and discuss further research issues.

• The Journal of Society for e-Business Studies
• /
• v.15 no.3
• /
• pp.1-23
• /
• 2010

It is crucially important to exchange and manage the financial information of an organization for the reason of complexity and diversity of information caused by its implicit information involved. Especially, according to the development of information technology, various approaches appeared to manage financial data of organization. For example, XBRL (Extensible Business Reporting Language) is one of the technologies dealing with the above criteria. Basically, XBRL is a business reporting language to define and exchange financial information, such as a financial statement of organization. XBRL is an international standard which enables the exchange of information between information providers and consumers by adding the tags involving the information of circumstantial factors of data. However, XBRL is not able to describe semantics because XBRL is fundamentally based on XML(Extensible Markup Language) having the purpose of expressing and structuring data. Therefore, this paper aims to enable semantic information to XBRL through the semantic technology. The objective of this paper is an ontologization of the knowledge to perform sharing, reusing, discovering, and inferring the knowledge described and conducted by XBRL. In order to achieve the above objective, this paper suggests the methodology for the ontologization of the category and instance document of XBRL. Furthermore, this paper points out the possibility of suggested methodology in a practical business through indicating the advantages of the knowledge described by XBRL.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2007.11a
• /
• pp.1288-1292
• /
• 2007

Mobile phone is necessary articles by increasing mobile communication now. People usually use the Mobile phone in any time and place. Ring tone of Mobile phone effect owner or other person. The sound level of Mobile phone ring tone could be considered as noise if it is too loud a specific situation. Manufacturing company improve ring tone of mobile phone better in consumer's perception. In this study, we record ring tone of mobile phone and estimated the complexity and nonlinear characteristics of the relation between subjective evaluation and sound metrics. Linear regression models were obtained for the subjective evaluation and sound quality metrics. Semantic Differential Method is used to study sound quality Evaluation. To analyze the sound quality of ring tone.

• Proceedings of the IEEK Conference
• /
• 2003.07b
• /
• pp.1015-1018
• /
• 2003

As increasing the size and complexity of hard-ware and software system, more efficient design methodology has been developed. Especially design-reuse technique enables fast system development via integrating existing hardware and software. For this technique available hardware/software should be prepared as component-based parts, adaptable to various systems. This paper introduces a component-based VHDL analyzer allowing to be embedded in other applications, such as simulator, synthesis tool, or smart editor. VHDL analyzer parses VHDL description input, and performs lexical, syntactic, semantic checking, and finally generates intermediate-form data as the result. VHDL has full-features of object-oriented language such as data abstraction, inheritance, and polymorphism. To support these features special analysis algorithm and intermediate form is required. This paper summarizes practical issues on implementing high-performance/quality VHDL analyzer and provides its solution that is based on the intensive experience of VHDL analyzer development.

• Language and Information
• /
• v.14 no.1
• /
• pp.1-24
• /
• 2010

The complexity of comparative constructions in each language has given challenges to both theoretical and computational analyses. This paper first identifies types of comparative constructions in Korean and discusses their main grammatical properties. It then builds a syntactic parser couched upon the typed feature structure grammar, HPSG and proposes a context-dependent interpretation for the comparison. To check the feasibility of the proposed analysis, we have implemented the grammar into the existing Korean Resource Grammar. The results show us that the grammar we have developed here is feasible enough to parse Korean comparative sentences and yield proper semantic representations though further development is needed for a finer model for contextual information.

• Proceedings of the KIEE Conference
• /
• 1988.07a
• /
• pp.675-678
• /
• 1988

This paper describes the method of syntactic-semantic pattern recognition and description for two dimensional object which is adjusted or changed in size and its orientation. To avoid the complexity and ambiguity which is arised in the case of syntactic or decision-theoretic method is used individually, an attributed grammar is introduced which applies computative attributes to pattern primitives, and then uses decision-theoretic method for attributes and syntactic method for pattern structure. A primitive extraction embedding parsing and grobal rule for classification is also applied for more effective pattern recognition and description.

• Journal of the Semiconductor & Display Technology
• /
• v.21 no.1
• /
• pp.1-4
• /
• 2022

As computers can express and utilize information in a semantic dimension different from the real world, humans have opened the door to the digital world and have played a pivotal role in the transformation of the human habitual environment. Using metaverse, it can be possible to predict concepts such as virtual currency, artificial intelligence, and virtual reality, which have now become possible for practical systemic visualization. In order to implement the metaverse in the realm of technology, it requires not only a multifaceted discussion on the platform, but also research on an architect that can include the intrinsic complexity of the metaverse. In this paper, we discuss the architecture for an open metaverse platform based on convergence wrapping that can converge various contents into one space, and propose a comprehensive platform design.

• Journal of Korean Elementary Science Education
• /
• v.39 no.3
• /
• pp.399-411
• /
• 2020

This study aims to explore how elementary students perceive and approach the issue of plastic debris in marine habitats by examining students' perspectives on the ecosystem and environmental solutions. The study was conducted to 143 Grade Four elementary school students in Seoul. After implementing two class-units on plastic waste, students' constructed responses on the problem of and solutions to plastic debris in marine habitats were collected. Data were analyzed through semantic network analysis and the keywords were visualized to reflect their relationships. Furthermore, students' responses on how they perceive environmental problems were further analyzed based on the following analysis criteria: students' perspectives on the ecosystem, the level of complexity of food chain(s), and the scope of their perspective. Also, student responses on environmental solutions were classified to be either at a personal or social level. Through semantic network analysis, keywords identified for students' perceptions on the problem were the sea, plastic, debris, animals, living things, humans, extinction, while keywords extracted for the solutions were plastic, debris, recycling, disposable, and I. Based on the analysis criteria, it was found that students were well aware of the food chain concept, could perceive the ecosystem as having comprised of both biotic and abiotic factors, and could approach the problem beyond the scope of the marine environment. Also, most students mentioned the solutions only at a personal level. Based on the findings, implications on how to move forward in educating environmental issues related to the ecosystem in science education is further discussed.

• Journal of Information Science Theory and Practice
• /
• v.7 no.4
• /
• pp.56-64
• /
• 2019

Planting intercropping in rubber plantations is another alternative for generating more income for farmers. However, farmers still lack the knowledge of choosing plants. In addition, information for decision making comes from many sources and is knowledge accumulated by the expert. Therefore, this research aims to create a decision support system for growing rubber trees for individual farmers. It aims to get the highest income and the lowest cost by using semantic web technology so that farmers can access knowledge at all times and reduce the risk of growing crops, and also support the decision supporting system (DSS) to be more intelligent. The integrated intercropping ontology and rule are a part of the decision-making process for selecting plants that is suitable for individual rubber plots. A list of suitable plants is important for decision variables in the allocation of planting areas for each type of plant for multiple purposes. This article presents designing and developing the intercropping ontology for DSS which defines a class based on the principle of intercropping in rubber plantations. It is grouped according to the characteristics and condition of the area of the farmer as a concept of the rubber plantation. It consists of the age of rubber tree, spacing between rows of rubber trees, and water sources for use in agriculture and soil group, including slope, drainage, depth of soil, etc. The use of ontology for recommended plants suitable for individual farmers makes a contribution to the knowledge management field. Besides being useful in DSS by offering options with accuracy, it also reduces the complexity of the problem by reducing decision variables and condition variables in the multi-objective optimization model of DSS.

• Journal of Software Engineering Society
• /
• v.26 no.4
• /
• pp.93-103
• /
• 2013

Complexity and maintenance cost of software increase as much as software has been evolved, therefore importance of software maintenance recently arise. There are many signs that are difficulties to maintain software, called bad smell, in a large-scale software. The bad smell should be removed to improve maintainability. Recently, many software refactoring methods have researched to terminate the bad smell. In this paper, we propose how to identify long parameter list, which causes bad smell, and how to solve the problem for increasing software maintainability. In our approach, we classify the parameters for creating new objects by measuring semantic similarity among them. This is evaluated by experienced software developers, and the result is statistically verified.