• The Korea Journal of Herbology
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• v.31 no.4
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• pp.93-100
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• 2016

Objectives : The internet is the most common method to investigate information. It is showed that 75.2% of Internet users of 20s had health information search experience. So this study is aim to understanding of interest of public about the herbal medicine using internet search query volume data.Methods : The Naver that is the top internet portal web service of the Republic of Korea has provided an Internet search query volume data from January 2007 to the current through the Naver data lab (http://datalab.naver.com) service. We have collected search query volume data which was provided by the Naver in 606 herbal medicine names and sorted the data by peak and total search volume.Results : The most frequently searched herbal medicines which has less bias and sorted by peak search volume is 'wasong (와송)'. And the most frequently searched herbal medicines which has less bias and sorted by total search volume is 'hasuo (하수오)'.Conclustions : This study is showed that the rank of interest of public about herbal medicines. Among the above herbal medicines, some herbal medicines had supply issue. And there are some other herbal medicines that had very little demand in Korean medicine market, but highly interested public. So it is necessary to monitor for these herbal medicines which is highly interested of the public. Furthermore if the reliability of the data obtained on the basis of these studies, it is possible to be utilizing herbal medicine monitoring service.

• The KIPS Transactions:PartD
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• v.11D no.2
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• pp.269-280
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• 2004

The Pyramid-Technique is based on mapping n-dimensional space data into one-dimensional data and expresses it as a B+-tree. By solving the problem of search time complexity the pyramid technique also prevents the effect of "phenomenon of dimensional curse" which is caused by treatment of hypercube range query in n-dimensional data space. The SPY-TEC applies the space division strategy in pyramid method and uses spherical range query suitable for similarity search so that Improves the search performance. However, nearest neighbor query is more efficient than range query because it is difficult to specify range in similarity search. Previously proposed index methods perform well only in the specific distribution of data. In this paper, we propose an efficient searching technique for nearest neighbor object using PdR-Tree suggested to improve the search performance for high dimensional data such as multimedia data. Test results, which uses simulation data with various distribution as well as real data, demonstrate that PdR-Tree surpasses both the Pyramid-Technique and SPY-TEC in views of search performance.rformance.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.271-281
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• 2006

Due to the development of Internet, number of online documents and the amount of web services are increasing dramatically. However, there are several procedures required, before you actually find what you were looking for. These procedures are necessary to Internet users, but it takes time to search. As a method to systematize and simplify this repetitive job, this paper suggests a DotQuery based interactive search agent. This agent enables a user to search, from his computer, a plenty of information through the DotQuery service. which includes natural languages. and it executes several procedures required instead. This agent also functions as a plug-in service within general web browsers such as Internet Explorer and decodes the DotQuery service. Then it analyzes the DotQuery from a user through its own program and acquires service results through multiple browsers of its own.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.294-297
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• 2005

Time series are comprehensively appeared and developed in many applications, ranging from science and technology to business and entertainrilent. Similarity search under time warping has attracted much interest between the time series in the large sequence databases. DTW (Dynamic Time Warping) is a robust distance measure and is superior to Euclidean distance for time series, allowing similarity matching although one of the sequences can elastic shift along the time axis. Nevertheless, it is more unfortunate that DTW has a quadratic time. Simultaneously the false dismissals are come forth since DTW distance does not satisfy the triangular inequality. In this paper, we propose an efficient range query algorithmbased on a new similarity search method under time warping. When our range query applies for this method, it can remove the significant non-qualify time series as early as possible before computing the accuracy DTW distance. Hence, it speeds up the calculation time and reduces the number of scanning the time series. Guaranteeing no false dismissals, the lower bounding function is advised that consistently underestimate the DTW distance and satisfy the triangular inequality. Through the experimental result, our range query algorithm outperforms the existing others.

• Journal of the Korean Society for information Management
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• v.26 no.4
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• pp.81-92
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• 2009

This paper proposes a technique for improving performance using word senses and user feedback in web information retrieval, compared with the retrieval based on ambiguous user query and index. Disambiguation using query word senses can eliminating the irrelevant pages from the search result. According to semantic categories of nouns which are used as index for retrieval, we build the word sense knowledge-base and categorize the web pages. It can improve the precision of retrieval system with user feedback deciding the query sense and information seeking behavior to pages.

• Journal of the Korean Society for information Management
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• v.16 no.2
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• pp.49-80
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• 1999

This study analyses the researches on automatic query modification, expansion and combination based on search results of natural language queries and gives a conceptual framework for the factors affecting the effectiveness of the relevance feedback. The operating and experimental systems based on the vector space model, the binary independence model and the inference net model are reviewed, and it is found that the effectiveness of query expansion is affected by conceptual models, algorithms for weighting terms and documents and selecting query terms to be added, size of relevant and non-relevant documents to be used and size of terms to be added in relevance feedback, query length, type and size of DBs, etc.

• Journal of Information Processing Systems
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• v.19 no.5
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• pp.602-613
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• 2023

High-quality image datasets are in high demand for various applications. With many online sources providing manually collected datasets, a persisting challenge is to fully automate the dataset collection process. In this study, we surveyed an automatic image dataset generation field through analyzing a collection of existing studies. Moreover, we examined fields that are closely related to automated dataset generation, such as query expansion, web scraping, and dataset quality. We assess how both noise and regional search engine differences can be addressed using an automated search query expansion focused on hypernyms, allowing for user-specific manual query expansion. Combining these aspects provides an outline of how a modern web scraping application can produce large-scale image datasets.

• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.209-220
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• 2017

As a semantic data is widely used in various applications such as Knowledge Bases and Semantic Web, needs for effective search over a large amount of RDF data have been increasing. Previous keyword search methods based on distinct root semantics only retrieve a set of answer trees having different root nodes. Thus, they often find answer trees with similar meanings or low query relevance together while those with the same root node cannot be retrieved together even if they have different meanings and high query relevance. We propose a new method to find diverse and relevant answers to the query by permitting duplication of root nodes among them. We present an efficient query processing algorithm using path indexes to find top-k answers given a maximum amount of root duplication a set of answer trees can have. We show by experiments using a real dataset that the proposed approach can produce effective answer trees which are less redundant in their content nodes and more relevant to the query than the previous method.

• The Transactions of the Korea Information Processing Society
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• v.4 no.9
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• pp.2173-2184
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• 1997

Among spatial queries handled in spatial database systems, nearest neighbor queries to find the nearest spatial object from the given locaion occur frequently. The number of searched nodes in an index must be minimized in order to increase the performance of nearest neighbor queries. An Existing approach considered only the processing of an nearest neighbor query in a two-dimensional search space and could not optimize the number of searched nodes accurately. In this paper, we propose the optimal search distance and prove its properties. The proposed optimal search distance is the measurement of a new search distance for accurately selecting the nodes which will be searched in processing nearest neighbor queries. We present an algorithm for processing the nearest neighbor query by applying the optimal search distance to R-trees and prove that the result of query processing is correcter than the existing approach.

• Journal of Korean Library and Information Science Society
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• v.40 no.4
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• pp.139-158
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• 2009

This paper used the network analysis method to analyse a variety of attributes of searcher's search behaviors which was appeared on search access log data. The results of this research are as follows. First, the structure of network represented depending on the similarity of the query that user had inputed. Second, we can find out the particular searchers who occupied in the central position in the network. Third, it showed that some query were shared with ego-searcher and alter searchers. Fourth, the total number of searchers can be divided into some sub-groups through the clustering analysis. The study reveals a new recommendation algorithm of associated searchers and search query through the social network analysis, and it will be capable of utilization.