• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.687-694
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• 2003

According to the rapid increase of multimedia data quantity recently, various means of video data search has been desired. In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic-based retrieval method can be available for various query of users. Currently existent contents-based video retrieval systems search by single method such as annotation-based or feature-based retrieval, and show low search efficiency and requires many efforts of system administrator or annotator form less perfect automatic processing. In this paper, we propose semantic-based video retrieval system which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted from query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method that propose. Therefore, we design the system that can heighten retrieval efficiency of video data through semantic-based retrieval.

• The Transactions of the Korea Information Processing Society
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• v.2 no.4
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• pp.443-452
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• 1995

Object-oriented database systems have been proposed as an effective solution for providing the data management facilities of complex applications. Proving this claim and the investigation of related issues such as query processing have been hampered by the absence of a formal object-oriented query model. In this paper, we not only define a query model based on aggregation inheritance but also develop semantic rewriting rules which are applied to equivalence preserving rewrite rules in algebraic expression of a query. Analyzing semantically the query model, the query model can be optimized to logically object-oriented query processing. And algebra expresstions of a query can be optimized by applying equivalence preserving rewrite rules.

• ETRI Journal
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• v.29 no.5
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• pp.545-558
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• 2007

This paper presents an efficient semantic service discovery scheme called UbiSearch for a large-scale ubiquitous computing environment. A semantic service discovery network in the semantic vector space is proposed where services that are semantically close to each other are mapped to nearby positions so that the similar services are registered in a cluster of resolvers. Using this mapping technique, the search space for a query is efficiently confined within a minimized cluster region while maintaining high accuracy in comparison to the centralized scheme. The proposed semantic service discovery network provides a number of novel features to evenly distribute service indexes to the resolvers and reduce the number of resolvers to visit. Our simulation study shows that UbiSearch provides good semantic searchability as compared to the centralized indexing system. At the same time, it supports scalable semantic queries with low communication overhead, balanced load distribution among resolvers for service registration and query processing, and personalized semantic matching.

• 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.

• 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.

• The Journal of Society for e-Business Studies
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• v.12 no.3
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• pp.211-234
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• 2007

In e-business, XML is a major format of data and it is essential to efficiently process queries against XML data. XML query caching has received much attention for query performance improvement. In employing XML query caching, some efficient technique of cache replacement is required. The previous techniques considered as a replacement unit either the whole query result or the path in the query result. The former is simple to employ but it is not efficient whereas the latter is more efficient and yet the size difference among the potential victims is large, and thus, efficiency of caching would be limited. In this paper, we propose a new technique where the element in the query result is are placement unit to overcome the limitations of the previous techniques. The proposed technique could enhance the cache efficiency to a great extent because it would not pick a victim whose size is too large to store a new cached item, the variance in the size of victims would be small, and the unused space of the cache storage would be small. A technique of XML semantic cache replacement is presented which is based on the replacement function that takes into account cache hit ratio, last access time, fetch time, size of XML semantic region, size of element in XML semantic region, etc. We implemented a prototype XML semantic cache system that employs the proposed technique, and conducted a detailed set of experiments over a LAN environment. The experimental results showed that our proposed technique outperformed the previous ones.

• Journal of KIISE:Databases
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• v.33 no.4
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• pp.363-371
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• 2006

In spite of computer's development, the present state of a lot of electronic documents overflowed it's going to be more difficult to get appropriate information. Therefore it's more important to get meaningful information than to focus on the speed of processing. Semantic web enables and intelligent processing by adding semantic meta data on your web documents. Also as the semantic web grows, the knowledge resource is more important. In this paper, we propose a RDF storage system using relational database model aimed at intelligent processing by adding semantic meta data on your web documents, also a query processor aimed at query processing through the storage system. By using relational model, we could overcome a weakness of object or memory model.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.2
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• pp.53-60
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• 2012

In this paper, we proposes a new document summarization method using the expanded query by wikipedia and the semantic feature representing inherent structure of document set. The proposed method can expand the query from user's initial query using the relevance feedback based on wikipedia in order to reflect the user require. It can well represent the inherent structure of documents using the semantic feature by the non-negative matrix factorization (NMF). In addition, it can reduce the semantic gap between the user require and the result of document summarization to extract the meaningful sentences using the expanded query and semantic features. The experimental results demonstrate that the proposed method achieves better performance than the other methods to summary document.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.953-957
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• 2009

This paper proposes a keyword-based query translation system for the semantic web. With the relationship between keywords and ontology structure information, the system converts keyword based queries into queries written by formal query language which is appropriate for the semantic web. As a result, casual web users could not only express queries easily but also obtain the better result.

• Journal of Digital Convergence
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• v.12 no.6
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• pp.245-252
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• 2014

Semantic search promises to provide more accurate result than present-day keyword matching-based search by using the knowledge base represented logically. But, the ordinary users don't know well the complex formal query language and schema of the knowledge base. So, the system should interpret the meaning of user's keywords. In this paper, we describe a user query interpretation system for the semantic retrieval of multimedia contents. Our system is ontological knowledge base-driven in the sense that the interpretation process is integrated into a unified structure around a knowledge base, which is built on domain ontologies.