• Journal of the Korea Society of Computer and Information
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• v.10 no.3 s.35
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• pp.229-236
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• 2005

The Semantic Web enables machines to achieve an effective retrieval, integration, and reuse of web resources. The keyword search method currently used has a limit to accurate search results because of a simple string matching method in web environment. This paper proposes an Ontology-Based Information Retrieval which can solve the problems and retrieve better search results through semantic relations. In this system, we implemented the Cultural Assets Ontology based on OWL with RDQL and Jena API. we also suggest a method to handle properties stored in a database.

• Journal of the Korea Society of Computer and Information
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• v.22 no.2
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• pp.97-104
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• 2017

In semantic information retrieval, we first need to build domain ontology and second, we need to convert the users' search keywords into a standard query such as SPARQL. In this paper, we propose a method that can automatically convert the users' search keywords into the SPARQL queries. Furthermore, our method can ensure effective performance in a specific domain such as law. Our method constructs the keyword history ontology by associating each keyword with a series of information when there are multiple keywords. The constructed ontology will convert keyword history ontology into SPARQL query. The automatic transformation method of SPARQL query proposed in the paper is converted into the query statement that is deemed the most appropriate by the user's intended keywords. Our study is based on the existing legal ontology constructions that supplement and reconstruct schema and use it as experiment. In addition, design and implementation of a semantic search tool based on legal domain and conduct experiments. Based on the method proposed in this paper, the semantic information retrieval based on the keyword is made possible in a legal domain. And, such a method can be applied to the other domains.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.3
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• pp.339-346
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• 2016

Semantic search recently been used in the search field. POI is one of the most essential information that make up the geographic information, and many of the geographic information system has POI search function as a basic. In this study, we propose POI semantic search using collective intelligence. For this, we designed and implemented service that constructs empirical information from tag and image, and provides an intuitive spatial navigation experience. For POI search, collective intelligence platform that many users can participate to collect variety information was designed and implemented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.684-686
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• 2014

It is difficult to effectively search and data management due to the increasing number of web is now. While Semantic Web technologies and the development of next-generation wepin this as a way to overcome them, and monopolize the domestic utilization is not overwhelming introduction to the Semantic Web technology is being used in existing search engines. This causes the development of the Semantic Web is becoming slower, and reluctant to use the Semantic Web users who use search engines as well. In this paper, compared to the currently used web and the next generation of the web, and why utilization is low compared to the search engine you are using an existing Web technology that uses the Semantic Web technology is a search engine, what research was that the inefficient because, as a RDF-based Semantic suggest how to improve the efficiency solved by designing the web.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.1-9
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• 2005

Today, according to tremendous development of B2B e-commerce, B2B e-marketplaces which accomplish various types of transactions through a number of buyers and sellers on online are embossed importantly. However, buyers are unable to search correct products because of inconsistency of product information between buyers and sellers. This paper solved this problem as semantic web technology. Semantic Web is an extension of current Web in which information is given well-defined meaning, better enabling computers and people to work in cooperation. The Semantic Web aims at machine-processable information. Its underlying technologies are RDF, RDF Schema, and ontology as the shared formal conceptualization of particular domains. In this paper, we present an implementation of Semantic Web enabled search system for B2B E-Marketplace domains. The system exploits OWL as the standard ontology language proposed by W3C and the Jena which is a Semantic Web toolkit, namely a Java framework writing Semantic Web applications. Finally, we summarize our experiences and discuss future research topics.

• The Journal of Korean Association of Computer Education
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• v.14 no.3
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• pp.37-49
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• 2011

A user can use resources on the Semantic Web using a Semantic Web browser. In order to utilize the functions of Semantic Web browsers in education, we compared the functions of well-known Semantic Web browsers such as Tabulator, Contextual Search Browser (CSB), Magpie, and Piggy Bank. In order to utilize Semantic Web browsers in education, a user needs to understand the features of each Semantic Web browser and our work can help both teachers and students. Tabulator is an RDF browser that can help to check whether resources can be used for learning and relevance of resources. CSB can be used to search educational resources using a conrtext file that contains the subjects of learning. It can also help learning by showing semantic web resources in the form of triple set as well as by supporting highlighting function. Magpie can help learners without basic knowledge on learning materials by providing interpretation based on a glossary file and related background knowledge. Piggy Bank supports conversion of web resources into semantic web resources and allows to browse semantic web resources in various views as well as to share semantic web resources.

• Journal of the Korea Society of Computer and Information
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• v.18 no.12
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• pp.91-101
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• 2013

One issue with keyword search in general is its ambiguity which can ultimately impact the effectiveness of the search in terms of the quality of the search results. This ambiguity is primarily due to the ambiguity of the contextual meaning of each term in the query. In addition to the query ambiguity itself, the relationships between the keywords in the search results are crucial for the proper interpretation of the search results by the user and should be clearly presented in the search results. We address the keyword search ambiguity issue by adapting some of the existing approaches for keyword mapping from the query terms to the schema terms/instances. The approaches we have adapted for term mapping capture both the syntactic similarity between the query keywords and the schema terms as well as the semantic similarity of the two and give better mappings and ultimately 50% raised accurate results. Finally, to address the last issue of lacking clear relationships among the terms appearing in the search results, our system has leveraged semantic web technologies in order to enrich the knowledgebase and to discover the relationships between the keywords.

• 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.

• Journal of Internet Computing and Services
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• v.13 no.1
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• pp.107-115
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• 2012

In recent Information Environment, various Multimedia contents are getting noticed. But, since these contents have various formats of representation and very wide range of information, it was difficult to retrieve contents that user wanted and to utilize it. To solve these problems, many studies presented draft standards for adding metadata to contents, and then, semantic search for contents had become available. Unfortunately, as the number of metadata standards and contents increased, the lack of interoperability between contents was begun and users are faced with difficulty of search contents again. To improve these problems, this paper supports interoperability between metadata standards and expands the semantic relationship between elements and proposes an ontology which is named TOFIC(The Ontology For Imagery Contents) for enhanced semantic search. In TOFIC, the semantic relationships between MPEG-7 and TV-Anytime are classified, and extended new semantics are defined. As a result, semantic search for multimedia contents is enhanced and it is possible to retrieve most of the multimedia contents that exist on the current information environment consistently. In addition, it supports enhanced content-based search for multimedia contents.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11S
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• pp.3399-3409
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• 1999

Information filtering for internet search, in which new information retrieval environment is given, is different from traditional methods such as bibliography information filtering, news-group and E-mail filtering. Therefore, we cannot expect high performance from the traditional information filtering models when they are applied to the new environment. To solve this problem, we inspect the characteristics of the new filtering environment, and propose a semantic-based filtering model which includes a new filtering method using WordNet. For extracting keywords from documents, this model uses the SDCC(Semantic Distance for Common Category) algorithm instead of the TF/IDF method usually used by traditional methods. The world sense ambiguation problem, which is one of causes dropping efficiency of internet search, is solved by this method. The semantic-based filtering model can filter web pages selectively with considering a user level and we show in this paper that it is more convenient for users to search information in internet by the proposed method than by traditional filtering methods.