• Journal of Information Technology Services
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• v.7 no.3
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• pp.253-269
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• 2008

In this paper, we present an application called Semantic Search which is built on different supporting technologies and is designed to improve traditional web searching. The Semantic Search is becoming crucial challenges on semantic web. The assessment and the implementation of the research on Semantic Search is not full-fledged whereas its research is highly interested. Also there exists only little research that offers a commercial use Semantic Search System that should be taken into the account in measuring the effectiveness of a Semantic Search System. This paper proposes an implementation and evaluation for the Semantic Search System. Firstly, we built Semantic Search System which includes a case of development and it's procedure. Secondly, We presented the measurement of our Semantic Search System's effectiveness. Finally, the evaluation offers useful implications to the researchers and practitioners to improve the research level to the commercial use.

• Korean Journal of Oriental Medicine
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• v.17 no.2
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• pp.57-62
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• 2011

We in this paper propose a semantic search system using the basic ontology in Korean medicine field. The basic ontology provides a formalization of medicinal materials, formulas, and diseases of Korean medicine. Recently, many studies for the semantic search system have been proposed. However, they do not support the semantic search and reasoning in the domain of Korean medicine because they do not have the Korean medicine ontology. Our system provides the semantic search features of semantic keyword recommendation, associated information browsing, and ontology reasoning based on the basic ontology. In addition, they also have the features of ontology search of a form of table and graph, synonym search, and external Open API supports. The general search engines usually provide search results for the simple keyword, while our system can also provide the associated information with respect to search results by using ontology so that can recommend more exact results to users.

• Journal of Information Technology Services
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• v.12 no.3
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• pp.389-404
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• 2013

Geospatial information, which is one of social overhead capital, is predicted as a core growing industry for the future. The production of geospatial information requires a huge budget, so it is very important objective of the policy for geospatial information to prevent the duplication of geospatial projects. In this paper, we proposed a semantic search system which extracts possible duplication of geospatial projects by using ontology for geospatial project administration. In order to achieve our goal, we suggested how to construct and utilize geospatial project ontology, and designed the architecture and process of the semantic search. Moreover, we showed how the suggested semantic search works with a duplicated projects search scenario. The suggested system enables a nonprofessional can easily search for duplicated projects, therefore we expect that our research contributes to effective and efficient duplication review process for geospatial projects.

• The Journal of the Korea Contents Association
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• v.12 no.12
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• pp.533-543
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• 2012

We in this paper propose a semantic search system based on Korean medicine ontology. Semantic search augments search results and improves search accuracy by understanding which concept denotes terms which users is trying to find. Our semantic search system also provides these semantic search capabilities. Moreover, search scenarios which is meaningful in Korean medicine are designed and implemented by analyzing the semantics of Korean medicine ontology. Therefore, our system can help users find the useful search results with respect to Korean medicine by providing the more meaningful information as well as the connected information in ontology.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.1
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• pp.91-103
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• 2010

This paper introduces efficient rule-based semantic search techniques to ontology-based knowledge commerce services. Primarily, the search techniques presented in this paper define rules of reasoning that are required for users to search using the concept of ontology, multiple characteristics, relations among concepts and data type. In addition, based on the defined rules, the rule-based reasoning techniques search ontology for knowledge commerce services. This paper explains the conversion rules of query which convert user's query language into semantic search words, and transitivity rules which enable users to search related tags, knowledge products and users. Rule-based sematic search techniques are also presented; these techniques comprise knowledge search modules that search ontology using validity examination of queries, query conversion modules for standardization and expansion of search words and rule-based reasoning. The techniques described in this paper can be applied to sematic knowledge search systems using tags, since transitivity reasoning, which uses tags, knowledge products, and relations among people, is possible. In addition, as related users can be searched using related tags, the techniques can also be employed to establish collaboration models or semantic communities.

• The Journal of Society for e-Business Studies
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• v.21 no.4
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• pp.1-14
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• 2016

Semantic search is known as a series of activities and techniques to improve the search accuracy by clearly understanding users' search intent without big cognitive efforts. Usually, semantic search engines requires ontology and semantic metadata to analyze user queries. However, building a particular ontology and semantic metadata intended for large amounts of data is a very time-consuming and costly task. This is why commercialization practices of semantic search are insufficient. In order to resolve this problem, we propose a novel semantic search method which takes advantage of our previous semantic tensor space model. Since each term is represented as the 2nd-order 'document-by-concept' tensor (i.e., matrix), and each concept as the 2nd-order 'document-by-term' tensor in the model, our proposed semantic search method does not require to build ontology. Nevertheless, through extensive experiments using the OHSUMED document collection and SCOPUS journal abstract data, we show that our proposed method outperforms the vector space model-based search method.

• The KIPS Transactions:PartB
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• v.13B no.5 s.108
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• pp.533-540
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• 2006

The semantic web environment promise semantic search of heterogeneous data from distributed web page. Semantic search would resuit in an overwhelming number of results for users is increased, therefore elevating the need for appropriate personalized ranking schemes. Culture Finder helps semantic web agents obtain personalized culture information. It extracts meta data for each web page(culture news, culture performance, culture exhibition), perform semantic search and compute result ranking point to base user profile. In order to work efficient, Culture Finder uses five major technique: Machine learning technique for generating user profile from user search behavior and meta data repository, an efficient semantic search system for semantic web agent, query analysis for representing query and query result, personalized ranking method to provide suitable search result to user, upper ontology for generating meta data. In this paper, we also present the structure used in the Culture Finder to support personalized search service.

• The KIPS Transactions:PartB
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• v.12B no.1 s.97
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• pp.91-100
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• 2005

It has been proposed diverse methods to use web information efficiently as the size of information is increasing. Most of search systems use a keyword-based method that mostly relies on syntactic information. They cannot utilize semantic information of documents and thus they could generate to users. To solve shortcoming in searching documents, a technique using the Semantic Web is suggested. A semantic web can find relevant information to users by employing metadata which are represented using standard ontologies. Each document is annotated with a metadata which can be reasoned by agents. In this paper, we propose a search system using semantic web technologies. Our semantic search system analyzes semantically questions that user input, and get resolution information that user want. To improve efficiency and accuracy of semantic search systems, this paper proposes DQL(DAML Query Language) engine that employs inference engine to execute reasoning and DQL converter that changes keyword form question of the user to DQL.

• Journal of Digital Convergence
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• v.11 no.2
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• pp.271-277
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• 2013

Typical semantic search query for Semantic search promises to provide more accurate result than present-day keyword matching-based search by using the knowledge base represented logically. Existing keyword-based retrieval system is Preference for the semantic interpretation of a user's query is not the meaning of the user keywords of interconnect, you can not search. In this paper, we propose a method that can provide accurate results to meet the user's search intent to user preference based evaluation by ranking search. The proposed scheme is Integrated ontology-based knowledge base built on the formal structure of the semantic interpretation process based on ontology knowledge base system.

• Journal of Intelligence and Information Systems
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• v.14 no.1
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• pp.67-84
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• 2008

This paper proposes a design and realization for the semantic search system. The proposed model includes three Architecture Layers of a Semantic Search System ; (they are conceptually named as) the Knowledge Acquisition, the Knowledge Representation and the Knowledge Utilization. Each of these three Layers are designed to interactively work together, so as to maximize the users' information needs. The Knowledge Acquisition Layer includes index and storage of Semantic Metadata from various source of web contents(eg : text, image, multimedia and so on). The Knowledge Representation Layer includes the ontology schema and instance, through the process of semantic search by ontology based query expansion. Finally, the Knowledge Utilization Layer includes the users to search query intuitively, and get its results without the users'knowledge of semantic web language or ontology. So far as the design and the realization of the semantic search site is concerned, the proposedsemantic search system will offer useful implications to the researchers and practitioners so as to improve the research level to the commercial use.