• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.11
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• pp.2073-2078
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• 2016

Recently, there have been many research that recognize the situation using sensors. However, sensor data collection and analysis are still lacking in integration. This is because the data generated by the sensor is difficult to match in terms of metadata and units. Therefore, a methodology for efficiently using data generated from various sensors is needed. In this paper, we propose a system that recognizes the location through information generated from a moving iBeacon. This system constructs the ontology with the data that can recognize the exact position when the patient wearing iBeacon moves in the room. This maps standard items and sensor items, and stores the results of filtering the detected values as knowledge. the system can extract efficient location information by recognizing the value generated by moving the patient carrying iBeacon through the ontology. This can be applied not only to beacons but also to other sensors, and it can be applied variously according to the ontology configuration.

• Journal of KIISE:Software and Applications
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• v.35 no.4
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• pp.219-233
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• 2008

This paper suggests an intelligent semantic blog model to systematically analyze and manage biogosphere with ontology as its conceptual knowledge base. In the model, the system managers may support users to easily find appropriate blog resources by tracking and analyzing various relationships between ontology - they may intelligently recommend Interest blog communities to relevant users by monitoring interaction activities in blogoshpere, dynamically grouping the communities with the ontology. To systematically specify the functionality of our model, 1) we first express the structure of blog resources in terms of objects and relationships between them and then 2) we formalize a set of operators designed to be applied to the resources. System queries are implemented by the combination of the operators.

• The KIPS Transactions:PartB
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• v.14B no.4
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• pp.295-302
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• 2007

It is very iterative and complicated work to enter the personal information every time one fills the form-based resume or one joins the new membership page on the internet. Although there are some systems that have the personal information on the computer and fill the membership page automatically, their accuracies are not often satisfactory in that the fields and their values do not match exactly. The research proposes and implements a system that has user's information on the computer and reasons and fills the information automatically that a membership web page(target page) requests using the personal information ontology. During the reasoning process, the target page is analyzed to extract the requested fields. Then the requested field names are converted to the standard field names using synonym ontology. The converted requested fields find the appropriate level in the personal information ontology using ontology match making to generate the final field value. The system not only finds the similar fields but also generates the exact field values by reasoning on the information ontology hierarchy. By experimenting with several membership pages on the web, the system showed higher accuracy over the existing systems. The system can be easily applicable to the cases where one iteratively fills the same information such as resume form.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.160-166
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• 2007

When a mail was given to users, each user's response could be different according to his or her preference. This paper presents a solution for this situation by constructing a user preferred ontology for anti-spam systems. To define an ontology for describing user behaviors, we applied associative classification mining to study preference information of users and their responses to emails. Generated classification rules can be represented in a formal ontology language. A user preferred ontology can explain why mail is decided to be spam or ron-spam in a meaningful way. We also suggest a new rule optimization procedure inspired from logic synthesis to improve comprehensibility and exclude redundant rules.

• Journal of Korean Medical classics
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• v.26 no.3
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• pp.127-139
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• 2013

Objectives : In the traditional oriental medicine, efforts to utilize the knowledge system so called Ontology have been achieved for systemic researches and efficient propagation of knowledge on oriental medicine. So far, in Korea, studies on drug ontology, pathological ontology, Cold Damage ontology and diagnostic ontology had been implemented, however, any development of ontology in the field of Acupuncture &, Moxibustion has not been achieved. Methods : We used Microsoft Access to collect terms in ZhenJiuJiaYiJing. The terms are related to human body area and structure. And then we built relationship of 'part of' and 'criterion of acupuncture point location' between the terms. Result & Conclusions : The terms used to explain acupuncture points in order to describe the position of acupuncture point name in ZhenJiuJiaYiJing were 8 words concerning different name of acupuncture point(穴名) 109, body part name(人體部位名稱) 150, meridian(經脈) 6 and structure(構造物).

• Journal of Digital Contents Society
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• v.9 no.2
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• pp.277-284
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• 2008

As the increasing of users' request about internet web service, the importance of ontology to construct semantic web is increasing now. Early Internet data processing was studied in the form of data integration through centralized ontology construction. However, because of distributed environment of internet, when integrating data of distributed site, it is required to integrate data of each site in terms of peer-to-peer data processing for corresponding to fast change of internet. In this paper, in distributed environment, we propose data processing method which construct ontology in each site with ontology language OWL. Furthermore, through relational representation of OWL, we propose the system containing distributed query processing for data constructed in different site with different method.

• Genomics & Informatics
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• v.13 no.1
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• pp.7-14
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• 2015

During recent years, there has been exponential growth in biological information. With the emergence of large datasets in biology, life scientists are encountering bottlenecks in handling the biological data. This study presents an integrated geographic information system (GIS)-ontology application for handling microbial genome data. The application uses a linear referencing technique as one of the GIS functionalities to represent genes as linear events on the genome layer, where users can define/change the attributes of genes in an event table and interactively see the gene events on a genome layer. Our application adopted ontology to portray and store genomic data in a semantic framework, which facilitates data-sharing among biology domains, applications, and experts. The application was developed in two steps. In the first step, the genome annotated data were prepared and stored in a MySQL database. The second step involved the connection of the database to both ArcGIS and $Prot{\acute{e}}g{\acute{e}}$ as the GIS engine and ontology platform, respectively. We have designed this application specifically to manage the genome-annotated data of rumen microbial populations. Such a GIS-ontology application offers powerful capabilities for visualizing, managing, reusing, sharing, and querying genome-related data.

• Journal of the Korean Society for information Management
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• v.21 no.4 s.54
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• pp.27-47
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• 2004

In this study, the experiment was made to transform the relationship among terms in a thesaurus to ontology language as search tools for multilingual text. As a result, the equivalent relationship in the thesaurus can be expressed by different ways in the ontology, such as equivalentClass, equivalentProperty, sameAS, and so on. On the other hand, the associative relationship can be represented by ObjectProperty, DatatypeProperty, and inverseOf. For this test, first of all, the descriptors assigned by AAT and the descriptors from bilingual thesaurus by ICCD were translated into Korean. Then, the facet was used for conceptual equivalence among terms from different languages. The result of the study showed that using rdf:Property in ontology was the most effective way of transforming multilingual thesaurus into ontology.

• The KIPS Transactions:PartD
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• v.14D no.4 s.114
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• pp.389-394
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• 2007

This study suggests that it dynamically generates semantic Web services from Java and C++ components in order to supporting semantic Web service by using ontology. And the semantic Web should enable greater access not only to content but also to services on the Web. It needs semantic service discovery for components. So, we add ontology-based framework to Web service generation system from components. Especially, components and ontologies are transformed UML model so that it makes WSDL documents to support a generation of dynamic Web service using object modeling. The main contribution of this study is to generate web service dynamically from components and to support semantic Web environment by using ontology. In other words, this study integrates semantic Web service based on ontology and CBD method.

• Genomics & Informatics
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• v.17 no.2
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• pp.20.1-20.5
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• 2019

Entity normalization, or entity linking in the general domain, is an information extraction task that aims to annotate/bind multiple words/expressions in raw text with semantic references, such as concepts of an ontology. An ontology consists minimally of a formally organized vocabulary or hierarchy of terms, which captures knowledge of a domain. Presently, machine-learning methods, often coupled with distributional representations, achieve good performance. However, these require large training datasets, which are not always available, especially for tasks in specialized domains. CONTES (CONcept-TErm System) is a supervised method that addresses entity normalization with ontology concepts using small training datasets. CONTES has some limitations, such as it does not scale well with very large ontologies, it tends to overgeneralize predictions, and it lacks valid representations for the out-of-vocabulary words. Here, we propose to assess different methods to reduce the dimensionality in the representation of the ontology. We also propose to calibrate parameters in order to make the predictions more accurate, and to address the problem of out-of-vocabulary words, with a specific method.