• Journal of Internet Computing and Services
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• v.8 no.5
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• pp.67-79
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• 2007

As the Web technologies and wired/wireless network are improved and various new multimedia services are introduced recently, need for searching multimedia including video data has been much increasing, The previous approaches for multimedia retrieval, however, do not make use of the relationships among semantic concepts contained in multimedia contents in an efficient way and provide only restricted search results, This paper proposes a multimedia retrieval system exploiting semantic relevancy of multimedia contents based on a domain ontology, We show the effectiveness of the proposed system by experiments on a prototype system we have developed. The proposed multimedia retrieval system can extend a given search keyword based on the relationships among the semantic concepts in the ontology and can find a wide range of multimedia contents having semantic relevancy to the input keyword. It also presents the results categorized by the semantic meaning and relevancy to the keyword derived from the ontology. Independency of domain ontology with respect to metadata on the multimedia contents is preserved in the proposed system architecture.

• Journal of the Korean Society for information Management
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• v.31 no.3
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• pp.181-200
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• 2014

This study aims to analyze and evaluate video search services of major search portals, Naver and Google Korea. In particular, this study analyzed characteristics such as collection distribution, yearly distribution, the ratio of redundant search results, the ratio of advertising, and the quality of videos. This study also evaluated relevance, credibility, and currency of video search results, and investigated the factors that influence relevance and credibility. Finally, types and characteristics of error results were analyzed. The results of this study show that the relevance of Google's video search results is higher than those of Naver, whereas currency of Naver's search results is somewhat higher than those of Google. Google has more high resolution videos than Naver, and Naver has more advertising than Google. Both Google and Naver return many redundant videos in the search results. The results of this study can be implemented to the portal's effective development of video search services.

• Journal of Korea Multimedia Society
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• v.12 no.10
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• pp.1499-1507
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• 2009

With the abundance of digital contents, the necessity of precise indexing technology is consistently required. To meet these requirements, the intelligent software entity needs to be the subject of information retrieval and the interoperability among intelligent entities including human must be supported. In this paper, we analyze the unifying framework for multi-modality indexing that Snoek and Worring proposed. Our work investigates the method of improving the authenticity of indexing information in contents-based automated indexing techniques. It supports the creation and control of abstracted high-level indexing information through ontological concepts of Semantic Web skills. Moreover, it attempts to present the fundamental model that allows interoperability between human and machine and between machine and machine. The memory-residence model of processing ontology is inappropriate in order to take-in an enormous amount of indexing information. The use of ontology repository and inference engine is required for consistent retrieval and reasoning of logically expressed knowledge. Our work presents an experiment for storing and retrieving the designed knowledge by using the Minerva ontology repository, which demonstrates satisfied techniques and efficient requirements. At last, the efficient indexing possibility with related research is also considered.

• Korean journal of communication and information
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• v.40
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• pp.45-79
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• 2007

This study explored three questions: (1) what are the motives of producing and using user-created contents (UCC, video clips which are produced and uploaded at various web sites by individuals), (2) what are the gratifications that users obtain from UCC, and (3) what are the differences of gratifications according to individual uses of UCC. A survey was conducted to 258 UCC users and data were factor-analyzed to find the dimensions of motives and gratifications. As for the motives of UCC uses, six factors were constructed: self-expression, private life, participation, information retrieval, rest, and entertainment, among which self-expression showed the largest variation. As for the gratifications, five factors were constructed: self-expression, rest, information retrieval, socializing, and entertainment.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.726-730
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• 2009

The proliferation of the web and digital photography has drastically increased multimedia data and has resulted in the need of the high quality internet service based on the moving picture like user generated contents(UGC). The keyword-based search on large scale images and video collections is too expensive and requires much manual intervention. Therefore the web search engine may provide the content-based retrieval on the multimedia data for search accuracy and customer satisfaction. In this paper, we propose a novel distributed index structure based on multiple length signature files according to data distribution. In addition, we describe how our scalable index technique can be used to find the nearest neighbors in the cluster environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2840-2861
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• 2020

The purpose of this survey-based study is to make an analysis of search engine users' behaviors on the Search Engine Results Pages (SERPs) based on the three demographic characteristics gender, age, and program studying. In this study, a questionnaire was designed with 12 closed-ended questions. Remaining questions other than the demographic characteristic related ones were about "tab", "advertisement", "spelling suggestion", "related query suggestion", "instant search suggestion", "video result", "image result", "pagination" and the amount of clicking results. The questionnaire was used and the data collected were analyzed with the descriptive statistics as well as the inferential statistics. 84.2% of the study population was reached. Some of the major results are as follows: Most of each demographic characteristic category (i.e. female, male, under-20, 20-24, above-24, English computer engineering, Turkish computer engineering, software engineering) have rarely or more click for tab, spelling suggestion, related query suggestion, instant search suggestion, video result, image result, and pagination. More than 50.0% of female category click advertisement rarely; however, for the others, 50.0% or more never click advertisement. For every demographic characteristic category, between 78.0% and 85.4% click 10 or fewer results. This study would be the first attempt with its complete content and design. Search engine providers and researchers would gain knowledge to user behaviors about the usage of the SERPs based on the demographic characteristics.

• Journal of Korea Multimedia Society
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• v.11 no.3
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• pp.315-322
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• 2008

Searching a location of the copied video in video database, signatures should be robust to video reediting, channel noise, time variation of frame rate. Several kinds of signatures has been proposed. Ordinal signature, one of them, is difficult to describe the spatial characteristics of frame due to the site of fixed window, $N{\times}N$, which is compute the average gray value. In this paper, I studied an algorithm of sequence matching in video copy detection for the copyright protection, employing the R-tree index method for retrieval and suggesting a robust ordinal signatures for the original video clips and the same signatures of the pirated video. Robust ordinal has a 2-dimensional vector structures that has a strong to the noise and the variation of the frame rate. Also, it express as MBR form in search space of R-tree. Moreover, I focus on building a video copy detection method into which content publishers register their valuable digital content. The video copy detection algorithms compares the web content to the registered content and notifies the content owners of illegal copies. Experimental results show the proposed method is improve the video matching rate and it has a characteristics of signature suitable to the large video databases.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.10
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• pp.351-356
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• 2014

Recently, automobile black boxes have evolved to support functionality to transfer videos stored in them into mobile phones via wireless network, from which the videos can be utilized for various purposes. This paper presents a method for automation of traffic violation reports using the automobile black boxes. When a traffic violation is captured by a black box, the proposed method helps a user to transfer the video capturing it into a mobile phone through a simple UI operation. With the video, an HTTP request to report the violation is automatically generated from the mobile phone, and then is transferred to a cyber-report center. We present a prototype system that implements the proposed method, and discuss several issues necessary to apply the method to real-world applications.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.224-231
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• 2013

Defining the concept of prominent audio content as the most informative audio content from the users' perspective within a given unstructured audio segment, we propose a simple but robust intensity-based attack/release pattern features to detect the prominent audio content. We also propose a web-based annotation procedure to retrieve users' subjective perception and annotated 18 hours of video clips across various genres, such as cartoon, movie, news, etc. The experiments with a linear classification method whose models are trained for speech, music, and sound effect demonstrate promising - but varying across the genres of programs - results (e.g., 86.7% weighted accuracy for speech-oriented talk shows and 49.3% weighted accuracy for {action movies}).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.1
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• pp.163-172
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• 2007

The web as global network includes text document, video, sound, etc and connects each distributed information using link Through development of web, it accumulates abundant information and the main is text based documents. Most of user use the web to retrieve information what they want. So, numerous researches have progressed to retrieve the text documents using the many methods, such as probability, statistics, vector similarity, Bayesian, and so on. These researches however, could not consider both the subject and the semantics of documents. As a result user have to find by their hand again. Especially, it is more hard to find the korean document because the researches of korean document classification is insufficient. So, to overcome the previous problems, we propose the korean document classification method for semantic retrieval. This method firstly, extracts TF value and RV value of concepts that is included in document, and maps into U-WIN that is korean vocabulary dictionary to select the topic of document. This method is possible to classify the document semantically and showed the efficiency through experiment.