• Management Science and Financial Engineering
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• v.16 no.2
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• pp.29-38
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• 2010

As the Internet is more embedded in people's lives, Internet users draw on new Internet applications to express themselves through "user-created content (UCC)." In addition, there is a noticeable shift from text-centered contents mainly posted on bulletin boards to multimedia contents such as images and videos on UCC web sites. The changes require different way of recommendations comparing to traditional products or contents recommendation on the Internet. This paper aims to design UCC recommendation methods with user behavior data and contents metadata such as tags and titles, and compare performances of the suggested methods. Real web logs data of a major Korean video UCC site was used to empirical experiments. The results of the experiments show that collaborative filtering technique based on similarity of UCC customers' preferences performs better than other content-based recommendation methods based on tag information and content metadata.

• Science of Emotion and Sensibility
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• v.7 no.4
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• pp.57-65
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• 2004

In this paper, we present a hybrid approach which incorporates color, texture and shape in content-based image retrieval. Colors in each image are clustered into a small number of representative colors. The feature descriptor consists of the representative colors and their percentages in the image. A similarity measure similar to the cumulative color histogram distance measure is defined for this descriptor. The co-occurrence matrix as a statistical method is used for texture analysis. An optimal set of five statistical functions are extracted from the co-occurrence matrix of each image, in order to render the feature vector for eachimage maximally informative. The edge information captured within edge histograms is extracted after a pre-processing phase that performs color transformation, quantization, and filtering. The features where thus extracted and stored within feature vectors and were later compared with an intersection-based method. The content-based retrieval system is tested to be effective in terms of retrieval and scalability through experimental results and precision-recall analysis.

• Journal of KIISE
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• v.43 no.11
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• pp.1188-1200
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• 2016

Recommendation systems play a significant role in providing personalized information to users, with enhanced satisfaction and reduced information overload. Since the mid-1990s, many studies have been conducted on recommendation systems, but few have examined the recommendations of information from people in the online social networking environment. In this paper, we present a hybrid recommendation method that combines both the traditional system of content-based techniques to improve specialization, and the recently developed system of social network-based techniques to best overcome a few limitations of the traditional techniques, such as the cold-start problem. By suggesting a state-of-the-art method, this research will help users in online social networks view more personalized information with less effort than before.

• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.105-112
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• 2002

In order to process video data effectively, we need to save its content on database and a content-based retrieval method which processes various queries of all users is required. In this paper, we present VRS(Video Retrieval System) which provides similarity query, SQBE(Scene Query By Example) query, and content-based retrieval by combining the feature-based retrieval and the annotation-based retrieval. The SQBE query makes it possible for a user to retrieve scones more exactly by inserting and deleting objects based on a retrieved scene. We proposed query language and query processing algorithm for SQBE query, and carried out performance evaluation on similarity retrieval. The proposed system is implemented with Visual C++ and Oracle.

• The Journal of the Korea Contents Association
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• v.20 no.3
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• pp.18-30
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• 2020

Recently, as graph-structured data is widely used in various fields such as social networks and semantic Webs, needs for an effective and efficient search on a large amount of graph data have been increasing. Previous keyword-based search methods often find results by considering only the relevance to a given query. However, they are likely to produce semantically similar results by selecting answers which have high query relevance but share the same content nodes. To improve the diversity of search results, we propose a top-k search method that finds a set of subtrees which are not only relevant but also diverse in terms of the content nodes by controlling their similarity. We define a criterion for a set of diverse answer trees and design two kinds of diversified top-k search algorithms which are based on incremental enumeration and A^⁎ heuristic search, respectively. We also suggest an improvement on the A^⁎ search algorithm to enhance its performance. We show by experiments using real data sets that the proposed heuristic search method can find relevant answers with diverse content nodes efficiently.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.1-13
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• 2023

YouTube has become a popular platform for vlogs. Among various forms of vlogs, office worker vlogs, in which a person engaged in a specific job shows his/her work environment and daily routine, are gaining popularity. Thus, focusing on office worker vlogs, the present research investigates the effects of office worker vlogs' characteristics (i.e., vlog content characteristics, vlogger characteristics) on the YouTube viewers' educational value of the vlog and their job engagement. Specifically, this research examines whether(1) vlog content characteristics (i.e., usefulness, accessibility, and vividness) and (2) vlogger characteristics (i.e., job similarity, credibility, and expertise) influence the YouTube viewers' educational value of the vlog. Moreover, this research examines how the YouTube viewers' educational value of the vlog affects their job engagement. With a sample of YouTube viewers of office worker vlogs (N = 215), structural equation modelling was implemented to investigate the relationships in the proposed model. The results indicate that (1) perceived usefulness of the office worker vlog is positively associated with the educational value of the vlog; (2) perceived accessibility of the office worker vlog is positively associated with the educational value of the vlog, albeit marginally significant; (3) perceived vividness of the office worker vlog is positively associated with the educational value of the vlog; (4) perceived job similarity to the office worker vlogger is positively associated with the educational value of the vlog; (5) perceived credibility of the office worker vlogger is positively associated with the educational value of the vlog; (6) perceived expertise of the office worker vlogger is positively associated with the educational value of the vlog; and (7) the educational value of the office worker vlog is positively associated with the YouTube viewers' job engagement. The findings provide important implications for the production and use of office worker vlog contents.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.8
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• pp.1358-1364
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• 2002

Presently, Multimedia data are increasing suddenly in broadcasting and internet fields. For retrieval of still images in multimedia database, content-based image retrieval system is implemented in this paper that user can retrieve similar objects from image database after choosing a wanted query region of object. As to extract color features from query image, we transform color to HSV with proposed method that similarity is obtained it through histogram intersection with database images after making histogram. Also, query image is transformed to gray image and induced to wavelet transformation by which spatial gray distribution and texture features are extracted using banded autocorrelogram and GLCM before having similarity values. And final similarity values is determined by adding two similarity values. In that, weight value is applied to each similarity value. We make up for defects by taking color image features but also gray image features from query image. Elevations of recall and precision are verified in experiment results.

• Journal of Software Assessment and Valuation
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• v.16 no.1
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• pp.13-19
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• 2020

It can be seen that the infringement of copyright cases is increasing as the society becomes more complex and advanced. During the software copyright dispute, there may be a dispute over whether the software is duplicated and made into upgraded software. In this paper, we intend to propose an analysis method for determining whether to upgrade software. For the software upgrade analysis, a software similarity analysis technique was used. The analysis program covers servers, management programs, and Raspberry PC programs. The first analysis confirms the correspondence between program creation information and content. In addition, it analyzes the similarity of functions and screen composition between the submitted program and the program installed in the field. The second comparative analysis compares and analyzes similarities by operating two programs in the same environment. As a result of comparative analysis, it was confirmed that the operation and configuration screens of the two programs were identical. Thus, minor differences were found in a few files, but it was confirmed that the two programs were mostly made using the same or almost similar source code. Therefore, this program can be judged as an upgrade program.

• 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.