• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.6
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• pp.701-708
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• 2005

Structuring mechanism, important to serve messages in post-office box structure, is to construct the hierarchy of classes according to the contents of message objects. This Paper Proposes $\alpha$-cut based genealogy grouping method to cluster a lot of structured objects in application domain. The proposed method decides the relationship first by semantic similarity relation and fuzzy relation, and then performs the grouping by operations of search( ), insert() and hierarchy(). This hierarchy structure makes it easy to process group-related processing tasks such as answering queries, discriminating objects, finding similarities among objects, etc. The proposed post-office box structure may be efficiently used to serve and manage message objects by the creation of groups. The Proposed method is tested for 5500 message objects and compared with other methods such as non-grouping, BGM, RGM, OGM.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.2
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• pp.296-301
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• 2012

Currently, in order to develop an intelligent search engine to help users retrieve information effectively, many metodes have been used. The effective retrieval methods of these methods use ontology technology. Ontology technology is the core of the Semantic Web. In the Semantic Web, ontology technology can be used to retrieve related information through the inference engine more accurately and simply on the Semantic Web. In this paper, we implement and design college information retrieval based on ontology to retrieve college class, graduate school class and person class. We have collected the hierarchy structure about the College, graduate school and person informations, and we have used protege editor of the ontology developing tool to design some ontologies with the College informations collected. We also tested the designed ontology with the Inference Engine(Pellet) of protege editor, and implemented college information retrieval system using Inference Engine(Jena) for web services.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.19-33
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• 2013

In this research, a proposed Dynamic Virtual Ontology using Tags (DyVOT) supports dynamic search of resources depending on user's requirements using tags from social web driven resources. It is general that the tags are defined by annotations of a series of described words by social users who usually tags social information resources such as web-page, images, u-tube, videos, etc. Therefore, tags are characterized and mirrored by information resources. Therefore, it is possible for tags as meta-data to match into some resources. Consequently, we can extract semantic relationships between tags owing to the dependency of relationships between tags as representatives of resources. However, to do this, there is limitation because there are allophonic synonym and homonym among tags that are usually marked by a series of words. Thus, research related to folksonomies using tags have been applied to classification of words by semantic-based allophonic synonym. In addition, some research are focusing on clustering and/or classification of resources by semantic-based relationships among tags. In spite of, there also is limitation of these research because these are focusing on semantic-based hyper/hypo relationships or clustering among tags without consideration of conceptual associative relationships between classified or clustered groups. It makes difficulty to effective searching resources depending on user requirements. In this research, the proposed DyVOT uses tags and constructs ontologyfor effective search. We assumed that tags are extracted from user requirements, which are used to construct multi sub-ontology as combinations of tags that are composed of a part of the tags or all. In addition, the proposed DyVOT constructs ontology which is based on hierarchical and associative relationships among tags for effective search of a solution. The ontology is composed of static- and dynamic-ontology. The static-ontology defines semantic-based hierarchical hyper/hypo relationships among tags as in (http://semanticcloud.sandra-siegel.de/) with a tree structure. From the static-ontology, the DyVOT extracts multi sub-ontology using multi sub-tag which are constructed by parts of tags. Finally, sub-ontology are constructed by hierarchy paths which contain the sub-tag. To create dynamic-ontology by the proposed DyVOT, it is necessary to define associative relationships among multi sub-ontology that are extracted from hierarchical relationships of static-ontology. The associative relationship is defined by shared resources between tags which are linked by multi sub-ontology. The association is measured by the degree of shared resources that are allocated into the tags of sub-ontology. If the value of association is larger than threshold value, then associative relationship among tags is newly created. The associative relationships are used to merge and construct new hierarchy the multi sub-ontology. To construct dynamic-ontology, it is essential to defined new class which is linked by two more sub-ontology, which is generated by merged tags which are highly associative by proving using shared resources. Thereby, the class is applied to generate new hierarchy with extracted multi sub-ontology to create a dynamic-ontology. The new class is settle down on the ontology. So, the newly created class needs to be belong to the dynamic-ontology. So, the class used to new hyper/hypo hierarchy relationship between the class and tags which are linked to multi sub-ontology. At last, DyVOT is developed by newly defined associative relationships which are extracted from hierarchical relationships among tags. Resources are matched into the DyVOT which narrows down search boundary and shrinks the search paths. Finally, we can create the DyVOT using the newly defined associative relationships. While static data catalog (Dean and Ghemawat, 2004; 2008) statically searches resources depending on user requirements, the proposed DyVOT dynamically searches resources using multi sub-ontology by parallel processing. In this light, the DyVOT supports improvement of correctness and agility of search and decreasing of search effort by reduction of search path.

• Journal of Communications and Networks
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• v.13 no.6
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• pp.567-582
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• 2011

The growing popularity of the Internet has caused the size and complexity of communications and computing systems to greatly increase in recent years. To alleviate this increased management complexity, novel autonomic management architectures have emerged, in which many automated components manage the network's resources in a distributed fashion. However, in order to achieve effective collaboration between these management components, they need to be able to efficiently exchange information in a timely fashion. In this article, we propose a context dissemination framework that addresses this problem. To achieve scalability, the management components are structured in a hierarchy. The framework facilitates the aggregation and translation of information as it is propagated through the hierarchy. Additionally, by way of semantics, context is filtered based on meaning and is disseminated intelligently according to dynamically changing context requirements. This significantly reduces the exchange of superfluous context and thus further increases scalability. The large size of modern federated cloud computing infrastructures, makes the presented context dissemination framework ideally suited to improve their management efficiency and scalability. The specific context requirements for the management of a cloud data center are identified, and our context dissemination approach is applied to it. Additionally, an extensive evaluation of the framework in a large-scale cloud data center scenario was performed in order to characterize the benefits of our approach, in terms of scalability and reasoning time.

• Asia pacific journal of information systems
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• v.8 no.1
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• pp.43-64
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• 1998

Cooperative query answering is a research effort to develop a fault-tolerant and intelligent database system using the semantic knowledge base constructed from the underlying database. Such knowledge base has two aspects of usage. One is supporting the cooperative query answering process for providing both an exact answer and neighborhood information relevant to a query. The other is supporting ongoing maintenance of the knowledge base for accommodating the changes in the knowledge content and database usage purpose. Existing studies have mostly focused on the cooperative query answering process but paid little attention to the dynamic knowledge base maintenance. This paper proposes a multi-level knowledge representation framework called Knowledge Abstraction Hierarchy(KAH) that can not only support cooperative query answering but also permit dynamic knowledge maintenance, On the basis of the KAH, a knowledge abstraction database is constructed on the relational data model and accommodates diverse knowledge maintenance needs and flexibly facilitates cooperative query answering. In terms of the knowledge maintenance, database operations are discussed for the cases where either the internal contents for a given KAH change or the structures of the KAH itself change. In terms of cooperative query answering, four types of vague queries are discussed, including approximate selection, approximate join, conceptual selection, and conceptual join. A prototype system has been implemented at KAIST and is being tested with a personnel database system to demonstrate the usefulness and practicality of the knowledge abstraction database in ordinary database application systems.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.5
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• pp.715-726
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• 2002

The purpose of this study was to investigate the visual sensibility of color combination for clothing. The color combination for clothing were divided into three types according to the color coordination. In each type, the stimulus was applied three combination method according to the chromatic color/chromatic color, the chromatic color/achromatic color, the achromatic color/achromatic color. As a result, 42 color combination for clothing were obtained. The survey has been done for the 42 color combination for clothing with 27 semantic differential hi-polar scales. The major findings of this research were as follows. 1. To explain the hierarchy of visual sensibility, two sensibility groups were classified, the first group being cute and bold sensibility and the second group being comfortable and soft sensibility. 2. As result of the factor analysis, 4 factors(attractiveness, cuteness, boldness, softness) were found to be constructing factors for visual sensibility of color combination for clothing. 3. To explain the hierarchy of visual sensibility, two sensibility groups were classified, the first group being cute and bold sensibility and the second group being comfortable and sort sensibility.

• The Transactions of the Korea Information Processing Society
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• v.6 no.2
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• pp.347-356
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• 1999

We present a method of thesaurus construction in order to produce semantic concept hierarchy of Korean nouns and implement a system for constructing the thesaurus in this paper. Multiple-step construction method is applied to this system which uses bottom-up and top-down method complementarily for solving the non-objectivity of word hierarchy, working speed, structural contradiction and incoherency of existing thesaurus. This system maintains objectivity using the meaning sentence of machine-readable dictionary and solves structural contradiction and incoherency with reference to existing thesaurus. We implement a developmental tool based on client/server system to construct thesaurus including massive entries as soon as possible and multiple client can work simultaneously.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.3
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• pp.364-372
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• 2000

Subcategorization, defining dependency relation between predicates and their complements, is an important source of knowledge for resolving syntactic and semantic ambiguities arising in analyzing sentences. This paper describes a Korean subcategorization dictionary, particularly annotated with semantic roles of complements coupled with thesaural semantic hierarchy as well as syntactic dependencies. For annotating roles, we defined 25 semantic roles associated with surface case markers that can be used to derive semantic structures directly from syntactic ones. In addition, we used more than 120,000 entries of thesaurus to specify concept markers of noun complements, and also used 47 and 17 predicate patterns for verbs and adjectives, respectively, to express dependency relation between predicates and their complements. Using a full-fledged thesaurus for specifying concept markers makes it possible to build an effective selectional restriction mechanism coupled with the subcategorization dictionary, and using the standard predicate patterns for specifying dependency relations makes it possible to avoid inconsistency in the results and to reduce the costs for constructing the dictionary. On the bases of these, we built a Korean subcategorization dictionary for frequently used 13,000 predicates found in corpora with the aid of a tool specially designed to support this task. An experimental result shows that this dictionary can provide 72.7% of predicates in corpora with appropriate subcategorization information.

• Journal of KIISE:Software and Applications
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• v.28 no.9
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• pp.688-698
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• 2001

A homonym could be disambiguated by anther words in the context such as nouns, predicates used with the homonym. This paper proposes a homonym disambiguation system based on statistical semantic information which is extracted from definitions in dictionary. The semantic information consists of nouns and predicates that are used with the homonym in definitions. In order to extract accurate semantic information, definitions are used with the homonym in definitions. In order to extract accurate semantic information, definitions are classified into two types. One has hyponym-hypernym relation between title word and head word (homonym) in definition. The hyponym-hypernym relation is one level semantic hierarchy and can be extended to deeper levels in order to overcome the problem of data sparseness. The other is the case that the homonym is used in the middle of definition. The system considers nouns and predicates simultaneously to disambiguate the homonym. Nine homonyms are examined in order to determine the weight of nouns and predicates which affect accrutacy of homonym disambiguation. From experiments using training corpus(definitions in dictionary), the average accruracy of homonym disamguation is 96.11% when the weight is 0.9 and 0.1 for noun and verb respectively. And another experiment to meaure the generality of the homonym disambiguation system results in the 80.73% average accuracy to 1,796 untraining sentences from Korean Information Base I and ETRI corpus.

• Korean Journal of Child Studies
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• v.14 no.2
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• pp.79-94
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• 1993

The purpose of this study was (1) to investigate whether linguistic contrast helps children map a new word into a specific semantic domain when a new word is introduced, (2) to examine the existence of a hierarchy of domains into which children will place a new word, (3) to examine whether children's existing lexicons affect how children map a new word. A total of 320 children from 3 to 6 years of age were drawn from Pusan, Korea. The children were divided into one of four age groups. There were 80 children in each age group. In each group, children were randomly assigned to one of four groups; the linguistic contrast group exposed to color, the linguistic contrast group exposed to shape, a label group and control group. All of the children were tested for production and comprehension of the new word. The results of this study were as follows; (1) The linguistic contrast helped children learn the meanings of a new word. Especially, children age 4 or more showed a significant effect for linguistic contrast; however, it was not sufficient to teach 3-year-old the correct, referent of a term. (2) There was a hierarchy of domains into which children mapped a new word. There was no significant effect for domains into which 3-year-old children mapped the new word, but from 4 years of age children showed a preference for assuming a new word refered to an object's shape rather than its color. (3) Children's existing lexicon had no effect, on how children comprehend a new word.