• Journal of Digital Contents Society
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• v.15 no.5
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• pp.603-612
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• 2014

To provide efficient and correct search results, ontology which use the structure of information, is considered as a main mechanism in the semantic web. Therefore, recent research in information retrieval and data construction have emphasized the use of ontologies as a data representation and search mechanism. In this paper, we propose a semantic search method using ontology to improve search ability in web environment. Ontology and knowledge base is used to represent semantic meaning of the data and provide related web documents and facts as results. Also, search result ranking mechanism is proposed. The mechanism use cardinality of the keyword in the contents and structural information of ontology. Experimental results with several query processing indicate that different coefficient value in the expression gives different results in sample ontology system and we propose appropriate values of the coefficient.

• Journal of Information Processing Systems
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• v.14 no.5
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• pp.1195-1214
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• 2018

Typical search engines may not be the most efficient means of returning images in accordance with user requirements. With the help of semantic web technology, it is possible to search through images more precisely in any required domain, because the images are annotated according to a custom-built ontology. With appropriate annotations, a search can then, return images according to the context. This paper reports on the design of a tourism ontology relevant to touristic images. In particular, the image features and the meaning of the images are described using various properties, along with other types of information relevant to tourist attractions using the OWL language. The methodology used is described, commencing with building an image and tourism corpus, creating the ontology, and developing the search engine. The system was tested through a case study involving the western region of Thailand. The user can search specifying the specific class of image or they can use text-based searches. The results are ranked using weighted scores based on kinds of properties. The precision and recall of the prototype system was measured to show its efficiency. User satisfaction was also evaluated, was also performed and was found to be high.

• Journal of Satellite, Information and Communications
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• v.7 no.3
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• pp.86-93
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• 2012

In this paper, we propose keyword search and ranking methods for OWL documents that describe metadata and ontology on the Semantic Web. The proposed keyword search method defines a unit of keyword search result as an information resource and expands a scope of query keyword to names of class and property or literal data. And we reflected derived information by inference in the keyword search by considering the elements of OWL documents such as hierarchical relationship of classes or properties and equal relationship of classes. In addition, our method can search a large number of information resources that are relevant to query keywords because of information resources indirectly associated with query keywords through semantic relationship. Our ranking method can improve user's search satisfaction because of involving a variety of factors in the ranking by considering the characteristics of OWL. The proposed methods can be used to retrieve digital contents, such as broadcast programs.

• The KIPS Transactions:PartD
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• v.13D no.4 s.107
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• pp.525-534
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• 2006

Ontology specifies the knowledge in a specific domain and defines the concepts of knowledge and the relationships between concepts. It is possible to provide the service based on the semantic web through the ontology. Therefore, to specify and define the knowledge in a specific domain, it is required to generate the ontology which conceptualizes the knowledge. Accordingly, to search the information of potential customers for home-delivery marketing of post office, we design the specific domain to generate the ontology based on the semantic web in this paper. And we propose how to retrieve the information, using the generated ontology. We implement the data search robot which collects the information based on the generated ontology. Also, we confirm that the ontology and the search robot perform the information retrieval exactly.

• Journal of Information Technology Services
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• v.17 no.2
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• pp.129-142
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• 2018

Recently, the number of patent applications have been increasing rapidly every year as the importance of protecting intellectual property rights becomes more important. Patents must be inventive and have novelty. Especially, the novelty implies that the corresponding invention is not the same as the previous invention. To confirm the novelty, prior art search must be conducted before and after the application. The target of prior art search should include not only Korean patents but also foreign patents. Search of foreign patents should be supported by multilingual search techniques. However, a dictionary-based naive approach shows a limitation because some technical concepts are represented in different terms according to each nation. For example, a Korean term and a Japanese term may not be synonym even though they represent the same technical concept. In this paper, we propose a new method to map semantic similarity between technical terms in Korean patents and Japanese patents. To investigate different representations in each nation for the same technical concept, we identified and analyzed pairs of patents those are mutually connected with priority claim relationship. By performing an experiment with real-world data, we showed that our approach can reveal semantically similar technical terms in other language successfully.

• Journal of information and communication convergence engineering
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• v.14 no.2
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• pp.97-105
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• 2016

With the increasing demand for interoperability among existing learning resource systems in order to enable the sharing of learning resources, such resources need to be annotated with ontologies that use different metadata standards. These different ontologies must be reconciled through ontology mediation, so as to cope with information heterogeneity problems, such as semantic and structural conflicts. In this paper, we propose an ontology-mapping technique using Semantic Web Rule Language (SWRL) to generate semantic mapping rules that integrate learning resources from different systems and that cope with semantic and structural conflicts. Reasoning rules are defined to support a semantic search for heterogeneous learning resources, which are deduced by rule-based inference. Experimental results demonstrate that the proposed approach enables the integration of learning resources originating from multiple sources and helps users to search across heterogeneous learning resource systems.

• Journal of Digital Contents Society
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• v.12 no.4
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• pp.429-436
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• 2011

Various documents, images, videos and other materials on the web has been increasing rapidly. Efficient search of those things has become an important topic. From keyword-based search, internet search has been transformed to semantic search which finds the implications and the relations between data elements. Many annotation processing systems manipulating the metadata for semantic search have been proposed. However, annotation data generated by different methods and forms are difficult to process integrated search between those systems. In this study, in order to resolve this problem, we categorized levels of many annotation documents, and we proposed the method to measure the similarity between the annotation documents. Similarity measure between annotation documents can be used for searching similar or related documents, images, and videos regardless of the forms of the source data.

• The Journal of Society for e-Business Studies
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• v.13 no.3
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• pp.85-101
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• 2008

The semantic web is taken as next generation standards of information exchange on the internet to overcome the limitations of the current web. To utilize the information on the semantic web, tools are required the functionality of query search and reasoning for the ontology. However, most of semantic web management tools cannot efficiently support the search for the complex query because they apply Triple-based storage structure about RDF metadata. We design the storage structure of the ontology in corresponding with the structure of ontology data and develop the search system(SMART-DLTriple) to support complex query search efficiently in this research. The performance of the system using new storage structure is evaluated to compare with the popular semantic web management systems. The proposed method and system make a contribution to enhancement of a practical ontology reasoning systems due to improved performance of the ontology search.

• Journal of KIISE:Databases
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• v.33 no.7
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• pp.682-692
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• 2006

Searching for gene products which have similar biological functions are crucial for bioinformatics. Modern day biological databases provide the functional description of gene products using Gene Ontology(GO). In this paper, we propose a technique for semantic similarity search for gene products using the GO annotation information. For this purpose, an information-theoretic measure for semantic similarity between gene products is defined. And an algorithm for semantic similarity search using this measure is proposed. We adapt Fagin's Threshold Algorithm to process the semantic similarity query as follows. First, we redefine the threshold for our measure. This is because our similarity function is not monotonic. Then cluster-skipping and the access ordering of the inverted index lists are proposed to reduce the number of disk accesses. Experiments with real GO and annotation data show that GORank is efficient and scalable.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.7
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• pp.1585-1600
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• 2009

The goal of Semantic Web is to provide efficient and effective semantic search and web services based on the machine-processable semantic information of web resources. Therefore, the process of creating and adding computer-understandable metadata for a variety of web contents, namely, semantic annotation is one of the fundamental technologies for the semantic web. Recently, in order to manage annotation metadata, direct approach for embedding metadata into the document is mainly used in semantic annotation. However, many semantic annotation tools for web documents have been mainly worked with HTML documents, and most of these tools do not support semantic search functionalities using the metadata. In this paper, based on these problems and previous works, we propose the Ontology-based Semantic Annotation tool(OSA) to efficiently support semantic annotation for web documents(such as HTML, PDF). We define a semantic annotation model that represents ontological-semantic information by using RDFS(RDF Schema). Based on XMP(eXtensible Metadata Platform) standard, the model is encoded directly into the document. By using OSA with XMP, user can perform semantic annotation on web documents which are able to keep compatibility for managing annotation metadata. Eventually, the integrated semantic annotation metadata can be used effectively in semantic search for a variety of web contents.