• Journal of Korean Library and Information Science Society
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• v.50 no.1
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• pp.273-291
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• 2019

This study aims to extend fundamental categories from Clause 11, "facet analysis" in International Standards for thesaurus(ISO 25964-1) by analyzing fundamental categories of Clause 11 and concept and their scope in a thesaurus of Clause 5. For to do this, the fundamental categories were established by adjusting partially and adding mental entities explicitly referencing the highest concepts(YAMATO which is the upper ontology of Mizoguchi, and ISO 2788) and existing fundamental categories(PMEST, FRBR group 3 entities, 13 categories in CRG). Also, established fundamental categories were reorganized and structured based on concreteness/abstraction of PMEST in Ranganathan and independence/dependence of YAMATO in Mizoguchi. And the upper categories were divided into independent and dependent entities. Under these entities 28 criteria are included in the independent ones and 2 criteria in the dependent ones. In the further study, the result of this study can be expected to reuse and refer as controlled vocabulary in the field like classification, taxonomies and thesauri where expected to utilize fundamental categories and as the high-level concept when constructing an ontology for information retrieval.

• Journal of Life Science
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• v.21 no.4
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• pp.554-560
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• 2011

This study was performed to investigate the effects of microbial augmentation on the biological treatment of paper mill wastewater. Three bacteria (KN11, KN13, KN27) capable of degrading aromatic compounds and a bacterial strain (GT21) producing an extracellular cellulase were isolated from soil and wastewater by selective enrichment culture. Through morphological, physiological, and biochemical taxonomies, isolated strains of KN11, KN13, KN27, and GT21 were identified as Acinetobacter sp., Neisseria sp., Bacillus sp., and Pseudomonas sp. and named Acinetobacter sp. KN11, Neisseria sp. KN13, Bacillus sp. KN27, and Pseudomonas sp. GT21, respectively. For analysis of non-biodegradable and chemical oxygen demand (COD)-increasing matter in a paper mill wastewater, we utilized GC/MS to detect aromatic compounds and their derivatives containing several substituted functional groups. The microbial augmentation, J30 formulated with the mixture of bacteria including Acinetobacter sp. KN11, Neisseria sp. KN13, Bacillus sp. KN27, and Pseudomonas sp. GT21, was used for the treatment of paper mill wastewater. The optimum temperature and pH for COD removal of the microbial augmentation, J30, were $30^{\circ}C$ and 7.5, respectively. For evaluation of the industrial applicability of the microbial augmentation, J30 in the pilot test, treatment efficiency was examined using paper mill wastewater. The microbial augmentation, J30, showed a COD removal rate of 87%. On the basis of the above results, we designed the wastewater treatment process of the activated sludge system.

• Journal of Intelligence and Information Systems
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• v.12 no.2
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• pp.33-48
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• 2006

The Semantic Web and its related technologies have been opening the era of information sharing via the Web. There are, however, several huddles still to overcome in the new era, and one of the major huddles is the issue of information integration, unless a single unified and huge ontology could be built and used which could address everything in the world. Particularly in the e-business area, the problem of information integration is of a great concern for product search and comparison at various Internet shopping sites and e-marketplaces. To overcome this problem, we proposed an ontology-driven mapping algorithm between heterogeneous product classification and description frameworks. We also peformed a comparative evaluation of the proposed mapping algorithm against a well-Down ontology mapping tool, PROMPT.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.33-54
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• 2010

The World Wide Web is transitioning from being a mere collection of documents that contain useful information toward providing a collection of services that perform useful tasks. The emerging Web service technology has been envisioned as the next technological wave and is expected to play an important role in this recent transformation of the Web. By providing interoperable interface standards for application-to-application communication, Web services can be combined with component based software development to promote application interaction both within and across enterprises. To make Web services for service-oriented computing operational, it is important that Web service repositories not only be well-structured but also provide efficient tools for developers to find reusable Web service components that meet their needs. As the potential of Web services for service-oriented computing is being widely recognized, the demand for effective Web service discovery mechanisms is concomitantly growing. A number of public Web service repositories have been proposed, but the Web service taxonomy generation has not been satisfactorily addressed. Unfortunately, most existing Web service taxonomies are either too rudimentary to be useful or too hard to be maintained. In this paper, we propose a Web service taxonomy generation framework that combines an artificial neural network based clustering techniques with descriptive label generating and leverages the semantics of the XML-based service specification in WSDL documents. We believe that this is one of the first attempts at applying data mining techniques in the Web service discovery domain. We have developed a prototype system based on the proposed framework using an unsupervised artificial neural network and empirically evaluated the proposed approach and tool using real Web service descriptions drawn from operational Web service repositories. We report on some preliminary results demonstrating the efficacy of the proposed approach.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.137-152
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• 2012

In the generation of Web 2.0, as many users start to make lots of web contents called user created contents by themselves, the World Wide Web is overflowing by countless information. Therefore, it becomes the key to find out meaningful information among lots of resources. Nowadays, the information retrieval is the most important thing throughout the whole field and several types of search services are developed and widely used in various fields to retrieve information that user really wants. Especially, the legal information search is one of the indispensable services in order to provide people with their convenience through searching the law necessary to their present situation as a channel getting knowledge about it. The Office of Legislation in Korea provides the Korean Law Information portal service to search the law information such as legislation, administrative rule, and judicial precedent from 2009, so people can conveniently find information related to the law. However, this service has limitation because the recent technology for search engine basically returns documents depending on whether the query is included in it or not as a search result. Therefore, it is really difficult to retrieve information related the law for general users who are not familiar with legal terms in the search engine using simple matching of keywords in spite of those kinds of efforts of the Office of Legislation in Korea, because there is a huge divergence between everyday words and legal terms which are especially from Chinese words. Generally, people try to access the law information using everyday words, so they have a difficulty to get the result that they exactly want. In this paper, we propose a term mapping methodology between everyday words and legal terms for general users who don't have sufficient background about legal terms, and we develop a search service that can provide the search results of law information from everyday words. This will be able to search the law information accurately without the knowledge of legal terminology. In other words, our research goal is to make a law information search system that general users are able to retrieval the law information with everyday words. First, this paper takes advantage of tags of internet blogs using the concept for collective intelligence to find out the term mapping relationship between everyday words and legal terms. In order to achieve our goal, we collect tags related to an everyday word from web blog posts. Generally, people add a non-hierarchical keyword or term like a synonym, especially called tag, in order to describe, classify, and manage their posts when they make any post in the internet blog. Second, the collected tags are clustered through the cluster analysis method, K-means. Then, we find a mapping relationship between an everyday word and a legal term using our estimation measure to select the fittest one that can match with an everyday word. Selected legal terms are given the definite relationship, and the relations between everyday words and legal terms are described using SKOS that is an ontology to describe the knowledge related to thesauri, classification schemes, taxonomies, and subject-heading. Thus, based on proposed mapping and searching methodologies, our legal information search system finds out a legal term mapped with user query and retrieves law information using a matched legal term, if users try to retrieve law information using an everyday word. Therefore, from our research, users can get exact results even if they do not have the knowledge related to legal terms. As a result of our research, we expect that general users who don't have professional legal background can conveniently and efficiently retrieve the legal information using everyday words.