• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.4
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• pp.95-102
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• 2004

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 md requires many efforts of system administrator or annotator because of imperfect automatic processing. In this paper, we propose semantics-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 and optimized comparison area extracting that propose. Therefore, we propose the system that can heighten retrieval efficiency of video data through semantics-based retrieval.

• Journal of the Korea Computer Industry Society
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• v.5 no.2
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• pp.203-216
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• 2004

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.

• Journal of Korea Multimedia Society
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• v.9 no.1
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• pp.127-137
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• 2006

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 automatic indexing 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 propose the system that can heighten retrieval efficiency of video data through semantic-based retrieval.

• 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 KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.803-810
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• 2005

Information retrieval is one of the most challenging areas in which the ontology technology is effectively used. Among them image retrieval using the image meta data and ontology is the one that can substitute the keyword-based image retrieval. In the paper, the retrieval of visual media such as the art image and photo picture is handled. It is assumed that there are more than one service providers of the visual media and also there is one central service broker that mediates the user's query. Given the user's query the first step that must be done in the service broker is to get the list of candidate service providers that fit the query. This is done by defining various ontologies such as the service ontology and matching the query against the ontology and providers. A novel matching method based on the ASN.1. The experiment shows that the method is more effective than existing tree-based and interval-based methods. Ontology merging issue is also handled that can happen when the service providers register their service into the service broker. An effective method is also proposed.

• The KIPS Transactions:PartD
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• v.16D no.2
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• pp.177-184
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• 2009

Environmental monitoring systems are widely developed for analyzing environment and understanding an ecosystem according to the advance of wireless communication and various sensing techniques. To extract useful information, it requires high cost for processing a query, because these systems have to handle huge volume of raw sensor data which is transmitted from a wide area in environmental monitoring applications. Besides, it is also hard to answer an user defined query which requests to check current and near future condition. In this paper, we propose the monitoring system structure for processing a user defined query for environmental monitoring. It also describes the utilization of sensor data filtering and abstraction model. The designed abstraction model which is based on the slope grid in GIS supports fast data access and update. To analyze condition, the extracted data from abstraction model of each sensor type is combined in a query processor. It is useful to provide meaningful information to users.

• Journal of the Korean Society for information Management
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• v.29 no.4
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• pp.101-121
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• 2012

Since IR systems which adopt only Boolean IR model can not provide ranked search result, users have to conduct time-consuming checking process for huge result sets one by one. This study proposes a method to provide search results ranked by using coupling information between tags instead of index weight information in Boolean IR model. Because document queries are used instead of general user queries in the proposed method, key tags used as queries in a relevant document are extracted. A variety of groups of Boolean queries based on tag couplings are created in the process of extracting queries. Ranked search result can be extracted through the process of matching conducted with differential information among the query groups and tag significance information. To prove the usability of the proposed method, the experiment was conducted to find research trend analysis information on selected research information. Aslo, the service based on the proposed methods was provided to get user feedback for a year. The result showed high user satisfaction.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.547-550
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• 2006

The criterion which judges an information retrieval system performance is to how many accurately retrieve an information that the user wants. The search result which uses only homograph has been appears the various documents that relates to each meaning of the word or intensively appears the documents that relates to specific meaning of it. So in this paper, we suggest semantic information retrieval technique using relation within User-Word Intelligent Network(U-WIN) to solve a disambiguation of query In our experiment, queries divide into two classes, the homograph used in terminology and the general homograph, and it sets the expansion query forms at "query + hypemym". Thus we found that only web document search's precision is average 73.5% and integrated search's precision is average 70% in two portal site. It means that U-WIN-Based semantic information retrieval technique can be used efficiently for a IR system.

• 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.

• The KIPS Transactions:PartB
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• v.18B no.4
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• pp.231-240
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• 2011

Many search algorithms have been implemented by many researchers on the world wide web. One of the best algorithms is Google using PageRank technology. PageRank approach computes the number of inlink of each documents then ranks documents in the order of inlink members. But it is difficult to find the results that user needs, because this method find documents not valueable for a person but valueable for the public. To solve this problem, We use the WordNet for analysis of the user's query history. This paper proposes a personalized search engine using the user's query history and PageRank Check. We compared the performance of the proposed approaches with google search results in the top 30. As a result, the average of the r-precision for the proposed approaches is about 60% and it is better as about 14%.