• Journal of Institute of Control, Robotics and Systems
• /
• v.18 no.11
• /
• pp.1027-1033
• /
• 2012

Semantic-based information retrieval techniques understand the meanings of the concepts that users specify in their queries, but the traditional semantic matching methods based on the ontology tree have three weaknesses which may lead to many false matches, causing the falling precision. In order to improve the matching precision and the recall of the information retrieval, this paper proposes a multi-agent improved semantic similarity matching algorithm based on the ontology tree, which can avoid the considerable computation redundancies and mismatching during the entire matching process. The results of the experiments performed on our algorithm show improvements in precision and recall compared with the information retrieval techniques based on the traditional semantic similarity matching methods.

• Proceedings of the Korea Contents Association Conference
• /
• 2004.11a
• /
• pp.265-268
• /
• 2004

Keyword matching technique which is used in most information retrieval systems is unfit for efficient processing of geometrically increasing information. The problem can be solved by using semantic information and an efficient method of semantic processing is introduced in this paper. The technique uses conceptual graph to represent the semantic information and apply it for information retrieval. The implemented system can perform exact matching and partial matching. Partial matching has two different types. One is syntactic partial matching and the other is semantic partial matching. The semantic semilaries are measured by the subclass relations in the ontology. The introduced technique can be used not only information retrieval but also in various applications such as an implementation of dynamic hyperlinks.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2005.04a
• /
• pp.680-687
• /
• 2005

This study presents a schema matching technique which can be applied to XML semantic model of structural calculation reports of steel-box bridges. The semantic model of structural calculation documents was developed by extracting the optimized common elements from the analyses of various existing structural calculation documents, and the standardized semantic model was schematized by using XML Schema. In addition, the similarity measure technique and the relaxation labeling technique were employed to develop the schema matching algorithm. The former takes into account the element categories and their features, and the latter considers the structural constraints in the semantic model. The standardized XML semantic model of steel-box bridge's structural calculation documents called target schema was compared with existing nonstandardized structural calculation documents called primitive schema by the developed schema matching algorithm Some application examples show the importance of the development of standardized target schema for structural calculation documents and the effectiveness and efficiency of schema matching technique in the examination of the degree of document standardization in structural calculation reports.

• Journal of Institute of Control, Robotics and Systems
• /
• v.22 no.9
• /
• pp.753-758
• /
• 2016

In this paper, we propose a novel method for estimating a vehicle's current position, even on roads that have similar patterns. In the proposed method, we classified the semantic information of the nodes in detail and added the semantic information of the link to solve the problem due to similar and repeated patterns. We also improved the mapping method by comparing the result of the duplicated matching with that of the only matching obtained just before corresponding duplicated matching. From the simulation results, we verify that the performance of the proposed method is better than that of the existing method.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.25 no.3
• /
• pp.595-602
• /
• 2015

One of the challenges of the digital forensics is how to handle certain amounts of data efficiently. Although reliable and various approximate matching algorithms have been presented to quickly identify similarities between digital objects, its practical effectiveness to identify the semantic similarity is low because of frequent false positives. To solve this problem, we suggest adding a pre-processing of the approximate matching target dataset to increase matching accuracy while maintaining the reliability of the approximate matching algorithm. To verify the effectiveness, we experimented with two datasets of eml and hwp using sdhash in order to identify the semantic similarity.

• The Journal of the Korea Contents Association
• /
• v.6 no.10
• /
• pp.25-33
• /
• 2006

For semantic retrieval in semantic web environment, it is an important factor to manage and manipulate distributed resources. Ontology is essential for efficient search in distributed resources, but it is almost impossible to construct an unified ontology for all distributed resources in the web. In this paper, we assumed that most information in the web environment exist in the form of RDBMS, and propose a matching method between domain ontology and the existing RDBMS tables for semantic retrieval. Most previous studies about matching between RDBMS tables and domain ontology have extracted a local ontology from RDBMS tables at first, and conducted the matching between the local ontology and domain ontology. However in the processing of extracting a local ontology, some problems such as losing domain information can be occurred since its correlation with domain ontology has not been considered at all. In this paper, we propose a methods to prevent the loss of domain information through the similarity measure between instances of RDBMS tables and instances of ontology. And using the relational information between RDBMS tables and the relational information between classes in domain ontology, more efficient instance-based matching becomes possible.

• KIPS Transactions on Software and Data Engineering
• /
• v.2 no.3
• /
• pp.173-186
• /
• 2013

Web-based map services provide various geographic information that users want to get by continuous updating of data. Those map services provide different information for a geographic object respectively. It causes several problems, and most of all various information cannot be integrated and provided. To resolve the problem, this paper proposes a system which can integrate diverse geographic information and provide users rich geographic information. In this paper, a hybrid schema matching (HSM) algorithm is proposed and the algorithm is a mixture of the adapter-based semantic processing method, static semantic management-based approach, and dynamic semantic management-based approach. A comparative evaluation is described to show effectiveness of the proposed algorithm. The proposed algorithm in this paper improves the accuracy of schema matching because of registration and management of schemas of new semantic information. The proposal enables vocabulary-based schema matching using various schemas, and it thus also supports high usability. Finally, the proposed algorithm is cost-effective by providing the progressive extension of relationships between schema meanings.

• The Journal of Society for e-Business Studies
• /
• v.14 no.2
• /
• pp.95-116
• /
• 2009

Ontologies have provided supports in integrating heterogeneous and distributed information. More and more ontologies and tools have been developed in various domains. However, building ontologies requires much time and effort. Therefore, ontologies need to be shared and reused among users. Specifically, finding the desired ontology from an ontology repository will benefit users. In the past, most of the studies on retrieving and ranking ontologies have mainly focused on lexical level supports. In those cases, it is impossible to find an ontology that includes concepts that users want to use at the semantic level. Most ontology libraries and ontology search engines have not provided semantic matching capability. Retrieving an ontology that users want to use requires a new ontology selection and ranking mechanism based on semantic similarity matching. We propose an ontology selection and ranking model consisting of selection criteria and metrics which are enhanced in semantic matching capabilities. The model we propose presents two novel features different from the previous research models. First, it enhances the ontology selection and ranking method practically and effectively by enabling semantic matching of taxonomy or relational linkage between concepts. Second, it identifies what measures should be used to rank ontologies in the given context and what weight should be assigned to each selection measure.

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

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2011.05a
• /
• pp.97-99
• /
• 2011

As interoperability between systems in distributed environment has been important, it has been possible for various organizations to share resources and exchange relevant information. However, semantic heterogeneity between the systems and organizations causes the problem of making their interoperability impossible. Thereby, in this paper, we propose an ontology matching-based knowledge management system which can automatically discover semantic correspondences between ontologies. Moreover, even though there have been many existing ontology matchers, it is still difficult to directly apply them to the proposed system. To deal with the problems, we want to discover matching patterns (MP) which they discover from two given ontologies.