• 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.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.89-97
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• 2011

In semantic web information system like ontology that access distributed information from network, efficient query processing requires an advanced caching mechanism to reduce the query response time. P2P network system have become an important infra structure in web environment. In P2P network system, when the query is initiated, reducing the demand of data transformation to source peer is important aspect of efficient query processing. Caching of query and query result takes a particular advantage by adding or removing a query term. Many of the answers may already be cached and can be delivered to the user right away. In web environment, semantic caching method has been proposed which manages the cache as a collection of semantic regions. In this paper, we propose the semantic caching technique in cluster environment of peers. Especially, using schema data filtering technique and schema similarity cache replacement method, we enhanced the query processing efficiency.

• Journal of Digital Convergence
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• v.11 no.3
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• pp.285-292
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• 2013

The method of recent information retrieval passes into an semantic search to provide more accurate results than keyword-based search. But in common user case, they are still accustomed to using existing keyword-based search. Hence they are hard to create a typed structured query language. In this paper, we propose to ontology knowledge-base scheme for query interpretation of these user. The proposed scheme was designed based on the OWL-DL for description logic reasoning, it can provide a richer representation of the relationship between the object by using SWRL(Semantic Web Rule Language). Finally, we are describe the experimental results of the similarity measurement for verification of a user query semantic interpretation.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.4
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• pp.11-20
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• 2010

Ontology is important role in semantic web to construct and query semantic data. Because of dynamic characteristic of ontology, P2P environment is considered for ontology processing in web environment. For efficient processing of ontology in P2P environment, clustering of peers should be considered. When new peer is added to the network, cluster allocation problem of the new peer is important for system efficiency. For clustering of peers with similar chateristics, similarlity measure method of ontology in added peer with ontologies in other clusters is needed. In this paper, we propose similarity measure techniques of ontologies for clustering of peers. Similarity measure method in this paper considered ontology's strucural characteristics like schema, class, property. Results of experiments show that ontologies of similar topics, class, property can be allocated to the same cluster.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.4
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• pp.382-387
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• 2014

Image retrieval is a procedure to find images based on the resemblance between query image and all images. In retrieving images, the crucial step that arises is how to define the similarity between images. In this paper, we propose a new similarity measure which is based on distribution of color. We apply the new measure to retrieving two different types of images, wallpaper images and the logo of automobiles, and compare its performance to other existing similarity measures.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.6
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• pp.2214-2218
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• 2010

Association rule is one of meaning and useful extraction methods from large amounts of data, and furnish useful information to user for data describing a pattern or similarity among attributes in database. Association rule have been studied about existence and nonexistence rule in boolean database. In this paper, we propose an intelligent query system using fuzzy association rule by extraction association rule changing a quantitative attribute data to a nominal attribute value.

• Journal of Information Technology Applications and Management
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• v.13 no.4
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• pp.121-140
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• 2006

UDDI (Universal Discovery Description and Integration) Registry is used for Web Services registration and search. UDDI offers the search result to the keyword-based query. UDDI supports WSDL registration but it does not supports WSDL search. So it is required that contents based search and ranking using name and description in UDDI registration information and WSDL. This paper proposes a retrieval engine considering contents of services registered in the UDDI and WSDL. It uses Vector Space Model for similarity comparison between contents of those. UDDI registry information hierarchy and WSDL hierarchy are considered during searching process. This engine suppports two discovery methods. One is Keyword-based search and the other is template-based search supporting ranking for user's query. Template-based search offers how service interfaces correspond to the query for WSDL documents. Proposed retrieval engine can offer search result more accurately than one which UDDI offers and it can retrieve WSDL which is registered in UDDI in detail.

• Journal of Digital Contents Society
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• v.10 no.2
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• pp.239-247
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• 2009

In simple topology in network system, query should be delivered to all linked peers for query processing. This causes waste of transmission band width and throughput of each peer. To overcome this, as well as query processing strategy, efficient routing technique to deliver query to proper peer is needed. For efficient routing, clustering of peers in P2P networks is important. Clustering of P2P network bases on that combines peers that have similar characteristics in same cluster reduces quantity of message in network than assign peer for cluster randomly. In this paper, we propose clustering techniques for ontology based P2P query processing. Similarity measure point, cluster index structure, and query processing steps in ontology based P2P cluster environment are proposed.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.8
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• pp.534-546
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• 2009

Query by humming is an effective and intuitive querying mechanism when a user wants to find a song without knowing lyrics. The query by humming system takes a user-hummed melody as input, compares it with melodies in a music database, and returns top-k similar melodies to the input. In this paper, we propose a novel algebra for query by humming, and design and implement a real query by humming system called HummingBase by exploiting the algebra. By analyzing existing similarity search techniques, we derive 10 core operators for the algebra. By using the well-defined algebra, we can easily implement such a system in a extensible and modular way. With two case studies, we show that the proposed algebra can easily represent the query processing processes of existing query-by-humming systems.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.181-188
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• 2006

In this paper, we propose a search algorithm for similar example-sentences in the computer-aided translation. The search for similar examples, which is a main part in the computer-aided translation, is to retrieve the most similar examples in the aspect of structural and semantical analogy for a given query from examples. The proposed algorithm is based on the Needleman-Wunsch algorithm, which is used to measure similarity between protein or nucleotide sequences in bioinformatics. If the original Needleman-Wunsch algorithm is applied to the search for similar sentences, it is likely to fail to find them since similarity is sensitive to word's inflectional components. Therefore, we use the lemma in addition to (typographical) surface information. In addition, we use the part-of-speech to capture the structural analogy. In other word, this paper proposes the similarity metric combining the surface, lemma, and part-of-speech information of a word. Finally, we present a search algorithm with the proposed metric and present pairs contributed to similarity between a query and a found example. Our algorithm shows good performance in the area of electricity and communication.