• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3102-3119
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• 2021

In the modern rapid growing web era, the scope of web publication is about accessing the web resources. Due to the increased size of web, the search engines face many challenges, in indexing the web pages as well as producing result to the user query. Methodologies discussed in literatures towards clustering web documents suffer in producing higher clustering accuracy. Problem is mitigated using, the proposed scheme, Semantic Conceptual Relational Similarity (SCRS) based clustering algorithm which, considers the relationship of any document in two ways, to measure the similarity. One is with the number of semantic relations of any document class covered by the input document and the second is the number of conceptual relation the input document covers towards any document class. With a given data set Ds, the method estimates the SCRS measure for each document Di towards available class of documents. As a result, a class with maximum SCRS is identified and the document is indexed on the selected class. The SCRS measure is measured according to the semantic relevancy of input document towards each document of any class. Similarly, the input query has been measured for Query Relational Semantic Score (QRSS) towards each class of documents. Based on the value of QRSS measure, the document class is identified, retrieved and ranked based on the QRSS measure to produce final population. In both the way, the semantic measures are estimated based on the concepts available in semantic ontology. The proposed method had risen efficient result in indexing as well as search efficiency also has been improved.

• The Journal of Information Systems
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• v.18 no.3
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• pp.327-349
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• 2009

Traditional keyword-based searching methods suffer from low accuracy and high complexity due to the rapid growth in the amount of information. Accordingly, many researchers attempt to implement a so-called semantic search which is based on the semantics of the user's query. Semantic information can be described using a semantic modeling language, such as Topic Map. In this paper, we propose a new method to map a topic map to a traditional Relational Database (RDB) without any information loss. Although there have been a few attempts to map topic maps to RDB, they have paid scant attention to handling multi-role topics. In this paper, we propose a new storage structure to map multi-role topics to traditional RDB. The proposed structure consists of a mapping table, role tables, and content tables. Additionally, we devise a query translator to convert a user's query to one appropriate to the proposed structure.

• Journal of KIISE:Databases
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• v.35 no.1
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• pp.44-53
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• 2008

According to the widespread use of ontology-based applications, it is critical to efficiently store and process semantic information. Even though several related systems have been developed, they have some limitations in perspectives of the volume of target semantic data, the performance of semantic query processing, and the semantic data maintenance. In this paper we propose the OWL-aware relational model for the ontology management system and SQL-based semantic query processing mechanism. Also, to verify the query processing performance, we show that the proposed query professing mechanism is more efficient than sesame.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.35-45
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• 2009

According to the widespread use of ontology documents, a management system which store ontology data and process queries is needed for retrieving semantic information efficiently. In this paper I propose a storage schema that stores and retrieves semantic web documents based on RDF/RDFS ontology language developed by W3C in a relational databases. Specially, the proposed storage schema is designed to retrieve efficiently hierarchy information and to increase efficiency of query processing. Also, I describe a mechanism to transform RQL semantic queries to SQL relational queries and build up database using MS-ACCESS and implement in this paper. According to the result of implementation, we can blow that not only data query based on triple model but also query for schema and hierarchy information are transformed simply to SQL.

• The Journal of Society for e-Business Studies
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• v.13 no.4
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• pp.209-222
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• 2008

The product information can be practically stored and managed, and also queried when we use a relational database. We need to develop a special indexing scheme in order to process the queries to ask for the semantic relationships of the product information. Such semantic relationships include ISA or taxonomy relationships that have the transitive properties. In this paper, we propose an index scheme to effectively process those queries with the transitive property. The proposed index scheme is based on a numbering scheme that has relatively low update cost.

• Journal of the Korea Society of Computer and Information
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• v.14 no.5
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• pp.1-9
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• 2009

Many techniques have been proposed to store efficiently and query XML data. One way achieving this goal is using relational database by transforming XML data into relational format. But most researches only transformed content and structure of XML schema. Although they transformed semantic constrainment of XML schema, they did not all of semantics. In this paper, we propose a systematic technique for extracting semantic constrainment from XML schema and storing method when the extracting result is transformed into relational schema without any lost of semantic constrainment. The transforming algorithm is used for extracting and storing semantic constrainment from XML schema and it shows how extracted information is stored according to schema notation. Also it provides semantic knowledges that are needed to be confirmed during the transformation to ensure a correct relation schema. The technique can reduce storage redundancy and can keep up content and structure with integrity constraints.

• Journal of Korea Multimedia Society
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• v.9 no.12
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• pp.1552-1559
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• 2006

In a web environment, similar information exists in many different places in diverse formats. Even duplicate information is stored in the various databases using different terminologies. Since most information serviced in the current World Wide Web however had been constructed before the advent of ontology, it is practically almost impossible to construct ontology for all those resources in the web. In this paper, we assume that most information in the web environment exist in the form of RDBMS, and propose a matching method between domain ontology and existing RDBMS tables for semantic retrieval. In the processing of extracting a local ontology, some problems such as losing domain in formation can occur since the correlation of domain ontology has not been considered at all. To prevent these problems, we propose an instance-based matching which uses relational information between RDBMS tables and relational information between classes in domain ontology. To verify the efficiency of the method proposed in this paper, several experiments are conducted using the digital heritage information currently serviced in the countrywide museums. Results show that the proposed method increase retrieval accuracy in terms of user relevance and satisfaction.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.1
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• pp.19-30
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• 2014

For the expansion of the Semantic Web, studies in converting the data stored in the relational database into the ontology are actively in process. Such studies mainly use an RDB to RDF mapping model, the model to map relational database components to RDF components. However, pre-proposed mapping models have got different expression modes and these damage the accessibility and reusability of the users. As a consequence, the necessity of the standardized mapping language was raised and the W3C suggested the R2RML as the standard mapping language for the RDB to RDF model. The R2RML has a characteristic that converts only the relational database schema data to RDF. For the same reasons above, the ontology about the relation data between table name and column name of the relational database cannot be added. In this paper, we propose an RDB to RDF mapping system considering semantic relations of RDB components in order to solve the above issue. The proposed system generates the mapping data by adding the RDFS attribute data into the schema data defined by the R2RML in the relational database. This mapping data converts the data stored in the relational database into RDF which includes the RDFS attribute data. In this paper, we implement the proposed system as a Java-based prototype, perform the experiment which converts the data stored in the relational database into RDF for the comparison evaluation purpose and compare the results against D2RQ, RDBToOnto and Morph. The proposed system expresses semantic relations which has richer converted ontology than any other studies and shows the best performance in data conversion time.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10a
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• pp.355-357
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• 1999

• Journal of Korean Society of Archives and Records Management
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• v.19 no.4
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• pp.63-86
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• 2019

UNESCO clearly has a good user interface compared to other sites. However, it does not have a structure in which user-centric knowledge curating is employed by users. As such, the knowledge structure should be expressed differently in advance for users to enjoy such benefits. At present, almost all current information systems are lacking with semantic and contextual information. Moreover, these systems are deemed insufficient of interlinking various kinds of thoughts in our minds. Thus, it is necessary to model in advance what users are likely to think and provide an interface that they can easily utilize based on that modeling. Furthermore, there is a need for a new structural theory based on semantic technology that can make that possible. Therefore, in this proposal, theoretical and practical insights were presented for user interface implementation to which relational facet navigation based on the structural theory is applied. Moreover, this proposal intends to suggest a "thinking expansion platform" that allows users' ideation of different concepts, including those unfamiliar to them.