• Journal of KIISE:Software and Applications
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• v.36 no.9
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• pp.732-748
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• 2009

The technology of Semantic Web realizes the base technology for context-awareness that creates new services by dynamically and flexibly combining various resources (people, concepts, etc). According to the realization of ubiquitous computing technology, many researchers are currently working for the embodiment of web service. However, most studies of them bring about the only predefined results those are limited to the initial description by service designer. In this paper, we propose a new service supporting model to provide an automatic method for plan related tasks which achieve goal state from initial state. The inputs on an planner are intial and goal descriptions which are mapped to the current situation and to the user request respectively. The idea of the method is to infer context from world model by DL-based ontology reasoning using OWL domain ontology. The context guide services to be loaded into planner. Then, the planner searches and plans at least one service to satisfy the goal state from initial state. This is STRIPS-style backward planner, and combine OWL-S services based on AI planning theory that enabling reduced search scope of huge web-service space. Also, when feasible service do not find using pattern matching, we give user alternative services through DL-based semantic searching. The experimental result demonstrates a new possibility for realizing dynamic service modeler, compared to OWLS-XPlan, which has been known as an effective application for service composition.

• Journal of KIISE
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• v.43 no.3
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• pp.370-379
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• 2016

Recently personal media were produced in a variety of ways as a lot of smart devices have been spread and services using these data have been desired. Therefore, research has been actively conducted for the media analysis and recognition technology and we can recognize the meaningful object from the media. The system using the media ontology has the disadvantage that can't classify the media appearing in the video because of the use of a video title, tags, and script information. In this paper, we propose a system to automatically classify video using the objects shown in the media data. To do this, we use a description logic-based reasoning and a rule-based inference for event processing which may vary in order. Description logic-based reasoning system proposed in this paper represents the relation of the objects in the media as activity ontology. We describe how to another rule-based reasoning system defines an event according to the order of the inference activity and order based reasoning system automatically classify the appropriate event to the category. To evaluate the efficiency of the proposed approach, we conducted an experiment using the media data classified as a valid category by the analysis of the Youtube video.

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

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.3
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• pp.409-414
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• 2013

With the increase of multimedia information such as images, researches have been realized on how to extract the high-level semantic information from low-level visual information, and a variety of techniques have been proposed to generate this information automatically. However, most of these technologies extract the semantic information between single images, it's difficult to extract semantic information when a combination of multiple objects within the image. In this paper, we extract the visual features of objects within the image and training images stored in the DB and the features of each object are defined by measuring the similarity. Using ontology reasoner, each object feature within images infers the semantic information by positional relation and associative relation. With this, it's possible to infer semantic information between objects within images, we proposed a method for inferring more complicated and a variety of high-level semantic information.

• Journal of the Korea Convergence Society
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• v.5 no.4
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• pp.147-153
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• 2014

To create a personal menu, there are a number of considerations. Personal menus are different depending on the dietary therapy for disease, diet for weight control. In addition, the menu you choose, depending on the personal preference and the season, the weather, current personal feelings may differ. An individual should expect to recommend a balanced diet, taking nutritional status just for health care. In this paper, we propose a personalized menu recommendations System framework to meet such needs. To recommend menus the system receives data of the body's individual circumstances, ingredients situation, environmental conditions, psychological condition, emotional condition and provides a recommended menu by performing the inference using the ontology generated from external application systems. In order to provide such services, Internet of Things (IoT) environment should be the foundation. In this paper, we propose a personalized diet recommendation system framework in the IoT standardization environment that has oneM2M common service platform.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.596-600
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• 2009

As the amount of available information increases rapidly, sometimes the efficient search method alone is not enough to obtain necessary information in timely manner. Therefore additional support is needed to share the burden of searching for and filtering information. In the area of ubiquitous computing, computer systems existing everywhere should be able to proactively provide information just in time. Resource matching is essential in order to develop a system searching and recommending information required for a user in a specific context. This paper describes the infrastructure and methodology of information providing including systematical organization representation, ontological resource demarcation, and resource matching in the environment of a research institute. A specific application was developed to illustrate the proposed approach.

• Journal of KIISE
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• v.44 no.10
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• pp.1045-1061
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• 2017

This paper suggests a method to expand linkages in a Linked Open Data(LOD) cloud that is a practical consequence of a semantic web. LOD cloud, contrary to the first expectation, has not been used actively because of the lack of linkages. Current method for establishing links by applying to explicit links and attaching the links to LODs have restrictions on reflecting target LODs' changes in a timely manner and maintaining them periodically. Instead of attaching them, this paper suggests that each LOD should prepare a link policy and publish it together with the LOD. The link policy specifies target LODs, predicate pairs, and similarity degrees to decide on the establishment of links. We have implemented a system that performs in-depth searching through LODs using their link policies. We have published APIs of the system to Github. Results of the experiment on the in-depth searching system with similarity degrees of 1.0 ~ 0.8 and depth level of 4 provides searching results that include 91% ~ 98% of the trustworthy links and about 170% of triples expanded.

• Journal of the Korean Society for information Management
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• v.22 no.3 s.57
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• pp.37-53
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• 2005

The terminology management is absolutely necessary for maintaining the efficiency of thesaurus. This is because the creating, differentiating, disappearing, and other processes of the descriptor become accomplished dynamically, making effective management of thesaurus a very difficult task. Therefore, a device is required for accomplishing methods to construct and maintain the thesaurus. This study proposes the methods to construct the thesaurus management using the basic elements of a topic map which are topic, occurrence, and association. Second, the study proposes the methods to represent the basic and specific instances using the systematic mapping algorithm and merging algorithm. Also, using a hub document as a standard, this study gives the methods to expand and subsitute the descriptors using the topic type. The new method applying fixed concept for double layer management on terms is developed, too. The purpose of this method is to fix the conceptual term which represents independent concept of time and space, and to select the descriptor freely by external information circumstance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.10
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• pp.2676-2683
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• 2009

The objective of this thesis is to improve the quality of a software product based on the enhancement of a software design quality using a better error detecting method. Also, this thesis is based on a software design method called as MOA(Methodology for Object to Agents) which uses an ontology based ODES(A Method based on Ontology for Detecting Errors in the Software Design) model as a common information model. At this thesis, a new format of error detecting method was defined. The method is implemented during a transformation process from UML model to ODES model using a ODES model, a Inter-View Inconsistency Detection technique and a combination of ontologic property of consistency framework and related rules. Transformation process to ODES model includes lexicon analysis and meaning analysis of a software design using of multiple mapping table at algorithm for the generation of ODES model instance.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.3
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• pp.221-225
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• 2009

Constructing an ontology using a mass corpus begins with an automatic semantic relation extraction. A general method regards words appearing between terms as patterns which are used to extract semantic relations. However, previous approaches consider only one sentence to extract a pattern, so they cannot extract semantic relations for terms in different sentences. This paper proposes a semantic relation extraction method using pairs of patterns sharing a term, where each pattern is extracted using one of the seed term pair satisfying the target relation. In our experiments, we achieved the accuracy 83.75% improving previous methods by 7.5% in is-${\alpha}$ relation and the accuracy 83.75% improved by 5% in part-of relation. We also present a possibility of improving the recall by the relative recall.