• 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.

• Journal of KIISE:Databases
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• v.37 no.4
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• pp.203-208
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• 2010

This paper deals with an efficient index scheduling technique based on Hilbert curve and MBR for k-NN query in a single wireless broadcast channel environment. Previous works have two major problems. One is that they need a long time to process queries due to the back-tracking problem. The other is that they have to download too many spatial data since they can not reduce search space rapidly. Our proposed method broadcasts spatial data based on Hilbert curve order where a distributed index table is also broadcast with each spatial data. Each entry of index table represents the MBR which groups spatial data. By predicting the unknown location of spatial data, our proposed index scheme allows mobile clients to remove unnecessary data and to reduce search space rapidly. As a result, our method gives the decreased tuning time and access latency.

• Journal of Creative Information Culture
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• v.7 no.3
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• pp.157-165
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• 2021

As the use of various application services utilizing Web and IoT and the need for large amounts of data management expand accordingly, the importance of efficient data expression and exchange scheme and data query processing is increasing. JSON, characterized by its simplicity, is being used in various fields as a format for data exchange and data storage instead of XML, which is a standard data expression and exchange language on the Web. This means that it is important to develop indexing and query processing techniques to effectively access and search large amounts of data expressed in JSON. Therefore, in this paper, we modeled JSON data with a hierarchical structure in a tree form, and proposed indexing and query processing using the path concept. In particular, we designed an index structure using a suffix array widely used in text search and introduced simple and complex path-based JSON data query processing methods.

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.715-725
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• 2020

In this paper, we propose an optimization scheme for a k-Nearest Neighbor(k-NN) query, which finds k objects closest to the query in the high dimensional feature vectors. The k-NN query is converted and processed into a range query based on the range that is likely to contain k data. In this paper, we propose an optimization scheme using DNN model to derive an optimal range that can reduce processing cost and accelerate search speed. The entire system of the proposed scheme is composed of online and offline modules. In the online module, a query is actually processed when it is issued from a client. In the offline module, an optimal range is derived for the query by using the DNN model and is delivered to the online module. It is shown through various performance evaluations that the proposed scheme outperforms the existing schemes.

• Journal of the Korean Society for information Management
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• v.23 no.2
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• pp.229-243
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• 2006

This study aims to suggest an effective way to enhance question-answer(QA) document retrieval performance by reconstructing queries based on the structural features in the QA documents. QA documents are a structured document which consists of three components : question from a questioner, short description on the question, answers chosen by the questioner. The study proposes the methods to reconstruct a new query using by two major structural parts, question and answer, and examines which component of a QA document could contribute to improve query performance. The major finding in this study is that to use answer document set is the most effective for reconstructing a new query. That is, queries reconstructed based on terms appeared on the answer document set provide the most relevant search results with reducing redundancy of retrieved documents.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5671-5693
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• 2017

With the rapid development of cloud computing, more and more data owners are motivated to outsource their data to cloud for various benefits. Due to serious privacy concerns, sensitive data should be encrypted before being outsourced to the cloud. However, this results that effective data utilization becomes a very challenging task, such as keyword search over ciphertexts. Although many searchable encryption methods have been proposed, they only support exact keyword search. Thus, misspelled keywords in the query will result in wrong or no matching. Very recently, a few methods extends the search capability to fuzzy keyword search. Some of them may result in inaccurate search results. The other methods need very large indexes which inevitably lead to low search efficiency. Additionally, the above fuzzy keyword search methods do not support access control. In our paper, we propose a searchable encryption method which achieves fuzzy search and access control through algorithm design and Ciphertext-Policy Attribute-based Encryption (CP-ABE). In our method, the index is small and the search results are accurate. We present word pattern which can be used to balance the search efficiency and privacy. Finally, we conduct extensive experiments and analyze the security of the proposed method.

• The Journal of the Korea Contents Association
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• v.12 no.8
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• pp.37-46
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• 2012

In the existing data dissemination methods for mobile P2P networks, the search performance of content that matches the peer profile is very excellent. However, in the search for content that does not match the their profile, additional consideration about case that contents does not match the profile is needed because costs for the query processing will be incurred. To solve these problems, we propose a new data dissemination method for efficient contents search in mobile P2P networks. In the proposed method, peers determine whether they experienced communications by using a timestamp message and then perform data dissemination. We also propose a ranking algorithm to efficiently store dissemination data in a limited memory. The proposed ranking method can reduce query messages by considering the profile matches, the distribution range, and the connectivity to the data distribution peer.