• Journal of the Korea Society of Computer and Information
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• v.26 no.5
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• pp.47-53
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• 2021

Sparse ratings data hinder reliable similarity computation between users, which degrades the performance of memory-based collaborative filtering techniques for recommender systems. Many works in the literature have been developed for solving this data sparsity problem, where the most simple and representative ones are the methods of utilizing Jaccard index. This index reflects the number of commonly rated items between two users and is mostly integrated into traditional similarity measures to compute similarity more accurately between the users. However, such integration is very straightforward with no consideration of the degree of data sparsity. This study suggests a novel idea of applying different similarity measures depending on the numeric value of Jaccard index between two users. Performance experiments are conducted to obtain optimal values of the parameters used by the proposed method and evaluate it in comparison with other relevant methods. As a result, the proposed demonstrates the best and comparable performance in prediction and recommendation accuracies.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.6
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• pp.390-394
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• 2016

This paper presents a new comparison method for haze-removal algorithms in next-generation automotive systems. Compared to previous peak signal-to-noise ratio-based comparisons, which measure similarity, the proposed modulation transfer function-based method checks sharpness to select a more suitable haze-removal algorithm for lane detection. Among the practical filtering schemes used for a haze-removal algorithm, experimental results show that Gaussian filtering effectively preserves the sharpness of road images, enhancing lane detection accuracy.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.3
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• pp.15-25
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• 2017

As the value and importance of softwares are growing up, software theft and piracy become a much larger problem. To tackle this problem, it is highly required to provide an accurate method for detecting software theft and piracy. Especially, while software theft is relatively easy in the case of Android applications (apps), screening illegal apps has not been properly performed in Android markets. In this paper, we propose a method to effectively measure the similarity between Android apps for detecting software theft at the executable file level. Our proposed method extracts method reference frequency and manifest information through static analysis of executable Android apps as the main features for similarity measurement. Each app is represented as an n-dimensional vectors with the features, and then cosine similarity is utilized as the similarity measure. We demonstrate the effectiveness of our proposed method by evaluating its accuracy in comparison with typical source code-based similarity measurement methods. As a result of the experiments for the Android apps whose source file and executable file are available side by side, we found that our similarity degree measured at the executable file level is almost equivalent to the existing well-known similarity degree measured at the source file level.

• Korean Institute of Interior Design Journal
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• no.16
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• pp.3-9
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• 1998

The purpose of this research is to empirically validate the IIPS (Interior Image Preference Scale) which is a newly developed visual instrument for evaluating the environmental disposition inherent to individuals especially one's interior image preferences. The questionnaire survey was used. The data were collected from Oct. 10th 1997 to Nov. 14th 1997. The subjects were 399 undergraduate students and 30 professor of Dep. of Interior Design. With respect to content validity and construct validity of IIPS discrimination and similarity structure of scales and characteristics of 12 prototype interior images were examined in comparison with the originals. 429 questionnaires were analyzed using frequency percentage mean and Multi-Dimensional Scales. The major results were as follows (1) All 80 items of IIPS were discriminated by 3 criteria such as Traditionalism·Modernity(TM) Masculinity·Femininty (MF) and Simplicity·Complexity (SC) as expected at the time of the instrument development stage.(2) 12 prototype interior images of the IIPS showed tendency to be accord with descriptors to express them in comparison with the originals (3) All 90 items of IIPS showed a cluster distribution according to the similarity structure of scales. Three subscales of IIPS(e . g. TM MF and SC) were structured pretty well by those 3 dimensions. This research revealed the IIPS to have content validity and construct validity for evaluating of preference of three properties of interior image in empirical research. The IIPS was found to be potential objective tool to measure the interior image preferences.

• Journal of the Korea Computer Industry Society
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• v.3 no.9
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• pp.1269-1278
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• 2002

The more high growth of knowledge, the more need personal identity technique. Fingerprint or iris of the eye identity techniques are already commercialized and used various field. Using human face recognition or authentication are not high performance yet. But application for an organism or face recognition are expected getting important. We propose a user recognition system by verifying similarity comparison of eye and lip component images which are splitted, calculated characteristic rate of each facial components and added weight to special formula. Through test proposed methods and analysis the result, we got a high recognition rate.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.2
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• pp.241-243
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• 2016

The recent spread of smart devices has led to creating a variety of services based on the smart device, and the needs for the user-centric services that fit the individual users according to their situations and characteristics are increasing. However, current services can not fulfil the individual requirement of individual user, because these services are intended for unspecified individual. This paper, as a key technology of automatic user-centric service mash-up considering the situation of individual user, investigated the similarity comparison method between the Open API parameters by calculating the amount of mutual information of the parameters extracted from the Open API documents.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.2
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• pp.357-367
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• 2018

As information technology of modern society develops, various malicious codes with the purpose of seizing or destroying important system information are developing together. Among them, ransomware is a typical malicious code that prevents access to user's resources. Although researches on detecting ransomware performing encryption have been conducted a lot in recent years, no additional methods have been proposed to recover damaged files after an attack. Also, because the similarity comparison technique was used without considering the repeated encryption, it is highly likely to be recognized as a normal behavior. Therefore, this paper implements a filter driver to control the file system and performs a similarity comparison method that is verified based on the analysis of the encryption pattern of the ransomware. We propose a system to detect the malicious process of the accessed process and recover the damaged file based on the cloud storage.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.3
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• pp.37-45
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• 2008

Quality assessment ai s to evaluate if a distorted image or video has a good quality by measuring the difference between the original and distorted images or videos. In this paper, to assess the visual qualify of a distorted image or video, visual features of the distorted image are compared with those of the original image instead of the direct comparison of the distorted image with the original image. We use edge projections from two images as features, where the edge projection can be easily obtained by projecting edge pixels in an edge map along vertical/horizontal direction. In this paper, edge projections are obtained by using vertical/horizontal directions of gradients as well as the magnitude of each gradient. Experimental results show the effectiveness of the proposed quality assessment through the comparison with conventional quality assessment algorithms such as structural similarity(SSIM), edge peak signal-to-noise ratio(EPSNR), and edge histogram descriptor(EHD) methods.

• Journal of Information Science Theory and Practice
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• v.7 no.1
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• pp.29-38
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• 2019

Information retrieval is the challenge of the Web 2.0 world. The experiment of knowledge organisation in the context of abundant information available from various sources proves a major hurdle in obtaining information retrieval with greater precision and recall. The fast-changing landscape of information organisation through social networking sites at a personal level creates a world of opportunities for data scientists and also library professionals to assimilate the social data with expert created data. Thus, folksonomies or social tags play a vital role in information organisation and retrieval. The comparison of these user-created tags with expert-created index terms, author keywords and title words, will throw light on the differentiation between these sets of data. Such comparative studies show revelation of a new set of terms to enhance subject access and reflect the extent of similarity between user-generated tags and other set of terms. The CiteULike tags extracted from 5,150 scholarly journal articles in marine science were compared with corresponding Aquatic Science and Fisheries Abstracts descriptors, author keywords, and title terms. The Jaccard similarity coefficient method was employed to compare the social tags with the above mentioned wordsets, and results proved the presence of user-generated keywords in Aquatic Science and Fisheries Abstracts descriptors, author keywords, and title words. While using information retrieval techniques like stemmer and lemmatization, the results were found to enhance keywords to subject access.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8649-8653
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• 2015

A number of video indexing and retrieval algorithms have been proposed to manage large video databases efficiently. The video similarity measure is one of most important technical factor for video content management system. In this paper, we propose the luminance characteristics model to measure the video similarity efficiently. Most algorithms for video indexing have been commonly used histograms, edges, or motion features, whereas in this paper, the proposed algorithm is employed an efficient similarity measure using the luminance projection. To index the video sequences effectively and to reduce the computational complexity, we calculate video similarity using the key frames extracted by the cumulative measure, and compare the set of key frames using the modified Hausdorff distance. Experimental results show that the proposed luminance projection model yields the remarkable improved accuracy and performance than the conventional algorithm such as the histogram comparison method, with the low computational complexity.