• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2211-2232
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• 2018

The unstructured and semi-structured big data in social network poses new challenges in query retrieval. This requirement needs to be met by introducing quality retrieval time measures like indexing. Due to the huge volume of data storage, there originate the need for efficient index algorithms to promote query processing. However, conventional algorithms fail to index the huge amount of frequently obtained information in real time and fall short of providing scalable indexing service. In this paper, a new LIndex algorithm, which is a heuristic on Lucene is built on Neo4jHA architecture that holds the social network Big data. LIndex is a flexible and simplified adaptive indexing scheme that ascendancy decomposed shortest paths around term neighbors as basic indexing unit. This newfangled index proves to be effectual in query space pruning of graph database Neo4j, scalable in index construction and deployment. A graph query is processed and optimized beyond the traditional Lucene in a time-based manner to a more efficient path method in LIndex. This advanced algorithm significantly reduces query fetch without compromising the quality of results in time. The experiments are conducted to confirm the efficiency of the proposed query retrieval in Neo4j graph NoSQL database.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.225-228
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• 2001

We propose a method which has effective scalable indexing characteristics of large color image archives. Color key and energy key method which uses provides high performance of fast accessing and has almost constant query response time over DH size.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.1
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• pp.9-20
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• 2005

Recently, the MPEG-7 standard a multimedia content description standard is wide]y used for content based image/video retrieval systems. However, since the descriptors standardized in MPEG-7 are usually multidimensional and the problem called 'Curse of dimensionality', previously proposed indexing methods(for example, multidimensional indexing methods, dimensionality reduction methods, filtering methods, and so on) could not be used to effectively index the multimedia database represented in MPEG-7. This paper proposes an efficient multimedia data indexing mechanism reflecting the characteristics of MPEG-7 visual descriptors. In the proposed indexing mechanism, the descriptor is transformed into a histogram of some attributes. By representing the value of each bin as a binary number, the histogram itself that is a visual descriptor for the object in multimedia database could be represented as a bit string. Bit strings for all objects in multimedia database are collected to form an index file, bitmap index, in the proposed indexing mechanism. By XORing them with the descriptors for query object, the candidate solutions for similarity search could be computed easily and they are checked again with query object to precisely compute the similarity with exact metric such as Ll-norm. These indexing and searching mechanisms are efficient because the filtering process is performed by simple bit-operation and it reduces the search space dramatically. Upon experimental results with more than 100,000 real images, the proposed indexing and searching mechanisms are about IS times faster than the sequential searching with more than 90% accuracy.

• The Journal of Society for e-Business Studies
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• v.3 no.2
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• pp.57-71
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• 1998

In this paper, we describe the approaches of shopping agents and directory services for online comparison shopping on the web, and propose an information indexing and retrieval system, named InfoEye, with a new method for automatic extraction of product information. The developed method is based on the knowledge about presentation of the product information on the Web. The method from the knowledge about presentation of the product information is derived from both the point that online stores display their products to customers in easy-to-browse ways and heuristics made of analyses of product information look-and-feel of domestic online stores. In indexing process, the method is applied to product information extraction from Hypertext Markup Language (HTML) documents collected by a mirroring robot from online stores. We have made InfoEye to a readily usable stage and transferred the technology to Webnara commercial shopping engine. The proposed system is a cutting-edge solution to help customers as a shopping expert by providing information about the reasonable price of a product from dozens of online stores, saving customers shopping time, giving information about new products, and comparing quality factors of products in a same category.

• The KIPS Transactions:PartD
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• v.9D no.5
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• pp.779-788
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• 2002

There are many technically difficult issues in searching multimedia data such as image, video and audio because they are massive and more complex than simple text-based data. As a method of searching multimedia data, a similarity retrieval has been studied to retrieve automatically basic features of multimedia data and to make a search among data with retrieved features because exact match is not adaptable to a matrix of features of multimedia. In this paper, data clustering and its indexing are proposed as a speedy similarity-retrieval method of multimedia data. This approach clusters similar images on adjacent disk cylinders and then builds Indexes to access the clusters. To minimize the search cost, the hashing is adapted to index cluster. In addition, to reduce I/O time, the proposed searching takes just one I/O to look up the location of the cluster containing similar object and one sequential file I/O to read in this cluster. The proposed schema solves the problem of multi-dimension by using clustering and its indexing and has higher search efficiency than the content-based image retrieval that uses only clustering or indexing structure.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.3
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• pp.149-159
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• 2008

We present new methods which transfer the color style of a source image into an arbitrary given reference image. Misidentification problem of color cause wrong indexing in low saturation. Therefore, the proposed method do indexing after Image separating chromatic and achromatic color from saturation. The proposed method is composed of the following four steps : In the first step, Image separate chromatic and achromatic color from saturation using threshold. In the second step, image of separation do indexing using cylindrical metric. In the third step, the number and positional dispersion of pixel decide the order of priority for each index color. And average and standard deviation of each index color be calculated. In the final step, color be transferred in Lab color space, and post processing to removal noise and pseudo-contour. Experimental results show that the proposed method is effective on indexing and color transfer.

• Journal of the Korean Society for information Management
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• v.26 no.3
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• pp.451-462
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• 2009

The aim of this study is to apply latent semantic indexing(LSI) techniques for efficient automatic classification of opinionated documents. For the experiments, we collected 1,000 opinionated documents such as reviews and news, with 500 among them labelled as positive documents and the remaining 500 as negative. In this study, sets of content words and sentiment words were extracted using a POS tagger in order to identify the optimal feature set in opinion classification. Findings addressed that it was more effective to employ LSI techniques than using a term indexing method in sentiment classification. The best performance was achieved by a supervised LSI technique.

• Journal of Korean Library and Information Science Society
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• v.2
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• pp.23-59
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• 1975

Indexes has not devcloped as an independent branch in library science from the beginning, but it has gradually evolved in a clo~eas sociation with catalog and under the direct influence of the development of publishing pro cesses and of the rapid social changes. Historically, index in the West can be traced back to eariler concordance. On the other hand, index in the Bast does not show a continuous development. It started with book catnlog, but other types of indexing were later 'adopted from the West. Indexing in the West and in the East can be summarized as follows: 1) In the West, Taylor considers Gesner's Pandectae was the first index but the Concordance of the Bible in 1247 was the first true index. Indexing method was first established later in 1545 in Gesner's Partitiones which appeared in three volumes. Classified index appeared after Partitions, but alphabetically ordered index was not developed until th eseventeenth century. The pxiodical index of La France S~auante in 1683 proved -its value, and Poole's An Alphabetical Index in the nineteenth century became the turning point in the development of indexing. After Poole's Index appeared periodical index and book catalog gradually began to be treated separately, and subject index and cross reference were incorporated into indexing. Also dictionary arrangement of the indexed items was adopted in the second half of the nincteenth, century after Charles A. Cutter developed his theory of rules for dictionary catalog and systematic studies of indexing were carried out by many scholars. In the twentieth century, index was mainly developed in the United States of America, especially by Wilson publishing Company. The general trend is to move away from the gcncral index to subject index. Also the ncwspapcr indcx such as The Times I~zdcx is 21 landmark in the history cf indcxing. 2) In China, thcs arc somc cvidcnccs that $Bizgluh(&), $ was the first indcx, but unforlunatcly the book itsclf has not been found as yet.

• The KIPS Transactions:PartD
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• v.15D no.2
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• pp.171-178
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• 2008

Since the XML standard was introduced by the W3C in 1998, documents that have been written in XML have been gradually increasing. Accordingly, several systems have been developed in order to efficiently manage and retrieve massive XML documents. BitCube-a bitmap indexing system-is a representative system for this field of research. Based on the bitmap indexing technique, the path bitmap indexing system(LH06), which performs the clustering of similar paths, improved the problem that the existing BitCube system could not solve, namely, determining similar paths. The path bitmap indexing system has the advantage of a higher retrieval speed in not only exactly matched path searching but also similar path searching. However, the similarity calculation algorithm of this system has a few particular problems. Consequently, it sometimes cannot calculate the similarity even though some of two paths have extremely similar relationships; further, it results in an increment in the number of meaningless clusters. In this paper, we have proposed a novel method that clustering, the similarity between the paths in order to solve these problems. The proposed system yields a stable result for clustering, and it obtains a high score in clustering precision during a performance evaluation against LH06.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.7
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• pp.713-717
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• 2008

Recently, as the capacity of flash memory increases rapidly, efficient indexing methods become crucial for fast searching of a large volume of data stored in flash memory. Flash memory has its unique characteristics: the write operation is much more costly than the read operation and in-place updating is not allowed. In this paper, we propose a novel index structure that significantly reduces the number of write operations and thus supports efficient searches, insertions, and deletions. We verify the superiority of our method by performing extensive experiments.