• Journal of Information Processing Systems
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• v.9 no.2
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• pp.315-332
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• 2013

This paper presents an approach for improving the use of VP-tree in video indexing and searching. A vantage-point tree or VP-tree is one of the metric space-based indexing methods used in multimedia database searches and data retrieval. Instead of relying on the Euclidean distance as a measure of search space, the proposed approach focuses on the trigonometric inequality for compressing the search range, which thus, improves the search performance. A test result of using 10,000 video files shows that this method reduced the search time by 5-12%, as compared to the existing method that uses the AESA algorithm.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.181-184
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• 2001

In recent, a morphological analyzer be used for indexing system in information retrieval system. A morphological analyzer as a indexing system must have multiprocessing ability to deal with multiple users and documents. To meet the needs of these, we propose a morphological analyzer with multi-threads method. To use multi-threads method, we consider memory allocation problem, threads synchronization problem, code optimization and so on. In this paper, first, we report several manners for multi-threads. And next, to evaluate our proposed system, we make a comparison test between proposed system and existing system.

• Proceedings of the Korea Database Society Conference
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• 1997.10a
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• pp.472-482
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• 1997

Multi-dimensional data play a crucial role in various fields, as like computer graphics, geographical information system, and multimedia applications. Indexing method fur multi-dimensional data Is a very Important factor in overall system performance. What is proposed in this paper is a new dynamic access method for spatial objects called HL-CIF(Hierarchically Layered Caltech Intermediate Form) tree which requires small amount of storage space and facilitates efficient query processing. HL-CIF tree is a combination of hierarchical management of spatial objects and CIF tree in which spatial objects and sub-regions are associated with representative points. HL-CIF tree adopts "centroid" of spatial objects as the representative point. By reflecting objects′sizes and positions in its structure, HL-CIF tree guarantees the high spatial locality of objects grouped in a sub-region rendering query processing more efficient.

• The Transactions of the Korea Information Processing Society
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• v.7 no.7
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• pp.2020-2027
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• 2000

The hypertext document is used for information exchange in the Web environments. Its structure is considered as having graph structures with links, which makes nonlinear processing of documents possible. This paper proposes an indexing method for information retrieval system using XML links. We define new attributes that control links of a remote document and assign an unique identifier for the attribute of each link. Each identifier has a different weight according to its occurrence position that is local or remote documents. We index a word not only from a local document but a remote document based on the given weight. Experimental results show that the proposed method outperforms conventional retrieval systems that ignore links.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.52-59
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• 2011

In this paper, we propose an indexing method to support efficient similarity search for sequence databases. We present a new distance measurement called minimum DTW distance to enhance the filtering effects. The minimum DTW distance is to measure the minimum distance between a sequence data and the group of similar sequences. It enables similarity search through hierarchical index structure by filtering sequence databases. Finally, we show the superiority of our method through some experiments.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1855-1858
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• 2003

In this paper, we propose image retrieval method more accurate and efficient than the conventional one. First of ail, we perform a shot detection and key frame extraction from the DC image constructed by DCT DC coefficients in the compressed video stream that is video compression standard such as MPEG[I][2]. We get principal axis applying PCA(Principal Component Analysis) to key frames for obtaining indexing information, and divide a domain. Video retrieval uses indexing information of high dimension. We apply KD-Trees(K Dimensional-Trees)[3] which shows efficient retrieval in data set of high dimension to video retrieval method. The proposed method can represent property of images more efficiently and property of domains more accurately using KD-Trees.

• The Journal of Information Systems
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• v.14 no.3
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• pp.37-47
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• 2005

Mining of association rules is to find associations among data items that appear together in some transactions or business activities. As of today, algorithms for association rule mining, as well as for other data mining tasks, are mostly applied to relational databases. As XML being adopted as the universal format for data storage and exchange, mining associations from XML data becomes an area of attention for researchers and developers. The challenge is that the semi-structured data format in XML is not directly suitable for traditional data mining algorithms and tools. In this paper we present an encoding method to encode XML tree-nodes. This method is used to store the XML data in Value Table and Transaction Table that can be easily accessed via indexing. The hierarchical relationship in the original XML tree structure is embedded in the encoding. We applied this method to association rules mining of XML data that may have missing data.

• Journal of Internet of Things and Convergence
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• v.1 no.1
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• pp.11-19
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• 2015

The mobile and ubiquitous environment is experiencing a rapid development of information and communications technology as it provides an ever increasing flow of information. Particularly, GIS is now widely applied in daily life due to its high accuracy and functionality. GIS information is utilized through the tiling method, which divides and manages large-scale map information. The tiling method manages map information and additional information to allow overlay, so as to facilitate quick access to tiled data. Unlike past studies, this paper proposes a new architecture and algorithms for tile searching and indexing management to optimize map information and additional information for GIS mobile applications. Since this involves the processing of large-scale information and continuous information changes, information is clustered for rapid processing. In addition, data size is minimized to overcome the constrained performance associated with mobile devices. Our system has been implemented in actual services, leading to a twofold increase in performance in terms of processing speed and mobile bandwidth.

• Spatial Information Research
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• v.20 no.2
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• pp.137-153
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• 2012

Until now, many indexing methods that can reduce update cost have been proposed for managing massive moving objects. Because indexing methods for moving objects have to be updated periodically for managing moving objects that change their location data frequently. However these kinds indexing methods occur big load that exceed system capacity when the number of moving objects increase dramatically. In this paper, we propose the update frequency reducing method to combine MapReduce and existing indices. We use the update request grouping method for each moving object by using MapReduce. We decide to update by comparing the latest data and the oldest data in grouping data. We reduce update frequency by updating the latest data only. When update is delayed, for the data should not be lost and updated periodically, we store the data in a certain period of time in the hash table that keep previous update data. By the performance evaluation, we can prove that the proposed method reduces the update frequency by comparison with methods that are not applied the proposed method.

• Journal of KIISE:Databases
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• v.32 no.3
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• pp.263-275
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• 2005

In a large DNA database, indexing techniques are widely used for rapid approximate sequence searching. However, most indexing techniques require a space larger than original databases, and also suffer from difficulties in seamless integration with DBMS. In this paper, we suggest a space-efficient and disk-based indexing and query processing algorithm for approximate DNA sequence searching, specially exact match queries, wildcard match queries, and k-mismatch queries. Our indexing method places a sliding window at every possible location of a DNA sequence and extracts its signature by considering the occurrence frequency of each nucleotide. It then stores a set of signatures using a multi-dimensional index, such as R*-tree. Especially, by assigning a weight to each position of a window, it prevents signatures from being concentrated around a few spots in index space. Our query processing algorithm converts a query sequence into a multi-dimensional rectangle and searches the index for the signatures overlapped with the rectangle. The experiments with real biological data sets revealed that the proposed method is at least three times, twice, and several orders of magnitude faster than the suffix-tree-based method in exact match, wildcard match, and k- mismatch, respectively.