• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.1
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• pp.125-136
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• 2007

The study on query relaxation which provides approximate answers has received attention. In recent years, some arguments have been made that semantic relationships are useful to present the relationships among data values and calculating the semantic distance between two data values can be used as a quantitative measure to express relative distance. The aim of this article is a hierarchical metricized knowledge abstraction (HiMKA) with an emphasis on combining data abstraction hierarchy and distance measure among data values. We propose the operations and the query relaxation algorithm appropriate to the HiMKA. With various experiments and comparison with other method, we show that the HiMKA is very useful for the quantified approximate query answering and our result is to offer a new methodological framework for query relaxation.

• Journal of KIISE:Software and Applications
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• v.30 no.1_2
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• pp.103-116
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• 2003

States explosion due to composition of spaces of data, temporal, and locational values is one of the well-known critical problems which cause difficulty in understanding and analysing real-time systems specified with state-based formal methods. In order to overcome this problem, this paper presents an abstraction method for state minimization based on an abstraction in system specification and an abstraction in system execution. The first is named the syntactic in system specification and an abstraction in system execution. The first is named the syntactic abstraction, through which the patterns of the unconditionally internalized computation and the repetition and selection structures are abstracted. The latter is named the semantic abstraction, through which the patterns of the execution space represented with data. Through the abstractions, the components of a system in specification and execution model is hierarchically organized. The system can be analyzed briefly in the upper level in an skeleton manner with low complexity. The system, however, can be abstraction method for the state minimization and the decrease in analysis complexity through the abstraction with examples.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.6
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• pp.727-731
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• 2010

Recently, mobile life-log data are collected by mobile devices and used to recode one's life. In order to help a user search data, a mobile life-log semantic network is introduced for storing logs and retrieving associative information. However, associative search systems on common semantic networks in previous studies provide for a user with only found data as text to users. This paper proposes an associative search system for mobile life-log semantic network that supports selection and keyword associative search of which a process and result are a visualized graph representing associative data and their relationships when a user inputs a keyword for search. In addition, by using semantic abstraction, the system improves user's understanding of search result and simplifies the resulting graph. The system's usability was tested by an experiment comparing the system and a text-based search system.

• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.1
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• pp.99-117
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• 1999

Since query language is used as a handy tool to obtain information from a database, a more intelligent query answering system is needed to provide user-friendly and fault-tolerant human-machine Interface. Frequently, database users prefer less rigid querying structure, one which allows for vagueness in composing queries, and want the system to understand the intent behind a query. When there is no matching data available, users would rather receive approximate answers than a null information response. This paper presents a knowledge abstraction database that facilitates the development of such a fault-tolerant and intelligent database system. The proposed knowledge abstraction database adepts a multilevel knowledge representation scheme called the knowledge abstraction hierarchy(KAH), extracts semantic data relationships from the underlying database, and provides query transformation mechanisms using query generalization and specialization steps. In cooperation with the underlying database, the knowledge abstraction database accepts vague queries and allows users to pose approximate queries as well as conceptually abstract queries. Specifically. 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 Intelligence and Information Systems
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• v.10 no.3
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• pp.91-103
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• 2004

Multi-agent systems for semantic web applications require efficient implementation of agent architectures without sacrificing the flexibility and the level of abstraction that agent architectures provide. In this paper, we present an agent system, called VivAce, which is implemented in Java to achieve both high efficiency and the level of abstraction provided by the BDI agent architecture. VivAce (Vivid Agent Computing Environment) has the characteristics of a vivid agent through the BDI agent model. A vivid agent is a software-controlled system whose state comprises the mental components of knowledge, perceptions, tasks, and intentions, and whose behavior is represented by means of action and reaction rules. We first identify the requirements for multi-agent systems and then present the relevant features of VivAce and experimental results.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2006.06a
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• pp.354-360
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• 2006

The purpose of this paper is to propose a securely personalized context-aware cooperative query that supports a multi-level data abstraction hierarchy and conceptual distance metric among data values, while considering privacy concerns around user context awareness. The conceptual distance expresses a semantic similarity among data values with a quantitative measure, and thus the conceptual distance enables query results to be ranked. To show the feasibility of the methodology proposed in this paper we have implemented a prototype system in the area of site search in a large-scale shopping mall.

• 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.

• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.761-766
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• 2005

This paper proposes a video model for the implementation of the cultural video database system. We have utilized an efficient scene change detection method that segments cultural video into semantic units for efficient indexing and retrieval of video. Since video has a large volume and needs to be played for a longer time, it implies difficulty of viewing the entire video. To solve this Problem. the cultural video abstraction was made to save the time and widen the choices of video the video abstract is the summarization of scenes, which includes important events produced by setting up the abstraction rule.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.2
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• pp.131-156
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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 on 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. The KAH consists of two types of knowledge abstraction hierarchies. The value abstraction hierarchy is constructed by abstract values that are hierarchically derived from specific data values in the underlying database on the basis of generalization and specialization relationships. The domain abstraction hierarchy is built on the various domains of the data values and incorporates the classification relationship between super-domains and sub-domains. 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, database operations are discussed for both the generalization and specialization Processes, and the conceptual query handling. A prototype system has been implemented at KAIST that demonstrates the usefulness of KAH in ordinary database application systems.

• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.87-96
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• 2006

Most conventional database systems support specific queries that are concerned only with data that match a query qualification precisely. A cooperative query answering supports query analysis, query relaxation and provides approximate answers as well as exact answers. The key problem in the cooperative answering is how to provide an approximate functionality for alphanumeric as well as categorical queries. In this paper, we propose a metricized knowledge abstraction hierarchy that supports multi-level data abstraction hierarchy and distance metric among data values. In order to facilitate the query relaxation, a knowledge representation framework has been adopted, which accommodates semantic relationships or distance metrics to represent similarities among data values. The numeric domains also compatibly incorporated in the knowledge abstraction hierarchy by calculating the distance between target record and neighbor records.