• Journal of the Korean Society for Library and Information Science
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• v.8
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• pp.73-101
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• 1981

Retrieval effectiveness is the principal criterion for measuring the performance of an information retrieval system. The effectiveness of a retrieval system depends primarily on the extent to which it can retrieve wanted documents without retrieving unwanted ones. So, ultimately, effectiveness is a function of the relevant and nonrelevant documents retrieved. Consequently, 'relevance' of information to the user's request has become one of the most fundamental concept encountered in the theory of information retrieval. Although there is at present no consensus as to how this notion should be defined, relevance has been widely used as a meaningful quantity and an adequate criterion for measures of the evaluation of retrieval effectiveness. The recall and precision among various parameters based on the 'two-by-two' table (or, contingency table) were major considerations in this paper, because it is assumed that recall and precision are sufficient for the measurement of effectiveness. Accordingly, different concepts of 'relevance' and 'pertinence' of documents to user requests and their proper usages were investigated even though the two terms have unfortunately been used rather loosely in the literature. In addition, a number of variables affecting the recall and precision values were discussed. Some conclusions derived from this study are as follows: Any notion of retrieval effectiveness is based on 'relevance' which itself is extremely difficult to define. Recall and precision are valuable concepts in the study of any information retrieval system. They are, however, not the only criteria by which a system may be judged. The recall-precision curve represents the average performance of any given system, and this may vary quite considerably in particular situations. Therefore, it is possible to some extent to vary the indexing policy, the indexing policy, the indexing language, or the search methodology to improve the performance of the system in terms of recall and precision. The 'inverse relationship' between average recall and precision could be accepted as the 'fundamental law of retrieval', and it should certainly be used as an aid to evaluation. Finally, there is a limit to the performance(in terms of effectiveness) achievable by an information retrieval system. That is : "Perfect retrieval is impossible."

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.53-59
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• 2021

When using Medical Information Retrieval services, a typical retrieval method is to use the Anatomic Therapyutic Chemical Classification (ATC) code. Traditional ATC code-based medical information retrieval is very useful for single ingredient product retrieval with single ingredient. However, in the case of complex, retrieval errors often occur. The cause of this problem is that ATC code-based retrieval proceeds by pattern matching ATC code.In this work, we design the mapping scheme based on ATC code by analyzing the requirement scenarios for retrieval based on main ingredient in ATC code-based retrieval. the mapping scheme based on ATC is a schema that stores the ATC code of the complex and all the ATC code of the single agent included in the complex. ATC code-based retrieval using this schema retrieves a complex as ingredient of a single ingredient product, thus having higher accuracy than existing methods. the mapping scheme based on ATC is expected to increase the efficiency of doctors' prescription of patients and increase the accuracy of drug safety use services.

• Journal of the Korean Society for information Management
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• v.19 no.1
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• pp.47-69
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• 2002

The concept based retrieval model has shown a higher performance than those of the simple matching function method or the P-norm retrieval method introduced to compensate the demerits of the Boolean retrieval model. However. it takes too long to create a semantic-net knowledge base, which is essential in concept exploration. In order to solve such demerits. a method was sought out by creating a distributed knowledge base by subjects to reduce construction time without hindering the performance of retrieval.

• Journal of the Korean Society for Library and Information Science
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• v.47 no.1
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• pp.39-55
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• 2013

It is a difficult problem to use keyword retrieval for low-quality Korean document images because these include adjacent characters that are connected. In addition, images that are created from various fonts are likely to be distorted during acquisition. In this paper, we propose and test a keyword retrieval system, using a support vector machine (SVM) for the retrieval of low-quality Korean document images. We propose a keyword retrieval method using an SVM to discriminate the similarity between two word images. We demonstrated that the proposed keyword retrieval method is more effective than the accumulated Optical Character Recognition (OCR)-based searching method. Moreover, using the SVM is better than Bayesian decision or artificial neural network for determining the similarity of two images.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.451-454
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• 2003

A new query method, called query by visual keys, is proposed to aim easy operation and efficient region-based image retrieval (RBIR). Visual keys are constructed from representative regions/subimages in a given image database, and the database is indexed with visual keys. A system on PC is presented, where text retrieval techniques are applied to the image retrieval with visual keys. Experimental results show that one retrieval is done within 4ms and that the proposed system achieves the comparable retrieval precision (with user-friendly operation and low computational cost) to conventional region based image retrieval systems

• Journal of the Korean Society for information Management
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• v.24 no.1 s.63
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• pp.103-120
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• 2007

Node is the semantic unit and a part of structured document. Information retrieval from structured documents offers an opportunity to go subdivided below the document level in search of relevant information, making any element in an structured document a retrievable unit. The node-based document retrieval constitutes several similarity calculating methods and the extended node retrieval method using structure information. Retrieval performance is hardly influenced by the methods for determining document similarity The extended node method outperformed the others as a whole.

• The Journal of the Korea Contents Association
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• v.7 no.1
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• pp.1-9
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• 2007

Semantic photo retrieval has been an important role in reducing the semantic gap between the simple visual features and the abundant semantics delivered by a photo. Effective photo retrieval using semantics is one of the major challenges in photo retrieval. And we propose a new event semantic photo retrieval method by using photo annotation user interface. In this paper, A photo album management system that facilitates photo management and semantic retrieval, which fully relies on the MPEG-7 standard as an information base and a native XML database, has been designed and implemented.

• Journal of Korean Library and Information Science Society
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• v.39 no.4
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• pp.261-281
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• 2008

This study surveyed the retrieval systems for digital information resources of the university libraries in Busan, Ulsan, Gyeongnam districts and the vendors. Kinds of access points and retrieval conditions (Boolean logic, methods of index term identification, and particularities of the retrieval) of the libraries' systems are various and different to each other. Access points of the vendors' systems are unessentially various and different to each other, but the retrieval conditions are rather elaborated. Upon the result the suggestions for the standardization of digital information retrieval system are offered.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.9C
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• pp.949-954
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• 2005

From the 90's, the image information retrieval methods have been on progress. As good examples of the methods, Conventional histogram method and merged-color histogram method were introduced. Dey could get good result in image retrieval. However, Conventional histogram method has disadvantages if the histogram is shifted as a result of intensity change. Merged-color histogram, also, causes more process so, it needs more time to retrieve images. In this paper, we propose an improved new method using Adaptive Color Histogram(ACH) in image retrieval. The proposed method has been tested and verified through a number of simulations using hundreds of images in a database. The simulation results have quickly yielded the highly accurate candidate images in comparison to other retrieval methods. We show that ACH's can give superior results to color histograms for image retrieval.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.11
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• pp.1059-1064
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• 2012

In this paper, some applications of natural language processing techniques for information retrieval have been introduced, but the results are known not to be satisfied. In order to find the roles of some classical natural language processing techniques in information retrieval and to find which one is better we compared the effects with the various natural language techniques for information retrieval precision, and the experiment results show that basic natural language processing techniques with small calculated consumption and simple implementation help a small for information retrieval. Senior high complexity of natural language processing techniques with high calculated consumption and low precision can not help the information retrieval precision even harmful to it, so the role of natural language understanding may be larger in the question answering system, automatic abstract and information extraction.