• Journal of Korea Society of Digital Industry and Information Management
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• v.4 no.2
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• pp.57-66
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• 2008

There have been proposed various copyright protection protocols in network-based digital multimedia distribution framework. However, most of conventional copyright protection protocols are focused on the stability of copyright information embedding/extracting and the access control to data suitable for user's authority but overlooked the privacy of copyright owner and user in authentication process of copyright and access information. In this paper, we propose a solution that builds a privacy-preserving proof of copyright ownership of digital contents in conjunction with keyword search scheme. The appeal of our proposal is three-fold: (1) content providers maintain stable copyright ownership in the distribution of digital contents; (2) the proof process of digital contents ownership is very secure in the view of preserving privacy; (3) the proposed protocol is the copyright protection protocol added by indexing process but is balanced privacy and efficiency concerns for its practical use.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10c
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• pp.550-552
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• 2004

분산 해시 테이블 (Distributed Hash Table) 을 사용한 P2P 시스템에서는 해시함수를 사용하며 파일과 노드의 ID를 정의하고 파일의 ID와 매핑 (mapping) 되는 ID를 가진 노드에 파일을 저장함으로써 시스템 전체에 파일을 완전히 분산시킨다. 이러한 시스템에서는 파일을 찾을 때 해시된 파일 ID로 찾기 때문에 정확한 매치 (exact match) 만 가능하다. 하지만 현재 P2P 파일 공유 시스템에서는 파일의 전체 이름을 정확히 알지 못하더라도 부분적인 키워드로 파일을 검색할 수 있도록 하는 키워드 검색 (keyword search) 이 요구된다. 본 논문에서는 분산 해시 테이블을 기반으로 하는 P2P 시스템에서 키워드 검색이 가능하도록 하는 방안을 제안한다.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.127-138
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• 2011

The core service of most research portal sites is providing relevant research papers to various researchers that match their research interests. This kind of service may only be effective and easy to use when a user can provide correct and concrete information about a paper such as the title, authors, and keywords. However, unfortunately, most users of this service are not acquainted with concrete bibliographic information. It implies that most users inevitably experience repeated trial and error attempts of keyword-based search. Especially, retrieving a relevant research paper is more difficult when a user is novice in the research domain and does not know appropriate keywords. In this case, a user should perform iterative searches as follows : i) perform an initial search with an arbitrary keyword, ii) acquire related keywords from the retrieved papers, and iii) perform another search again with the acquired keywords. This usage pattern implies that the level of service quality and user satisfaction of a portal site are strongly affected by the level of keyword management and searching mechanism. To overcome this kind of inefficiency, some leading research portal sites adopt the association rule mining-based keyword recommendation service that is similar to the product recommendation of online shopping malls. However, keyword recommendation only based on association analysis has limitation that it can show only a simple and direct relationship between two keywords. In other words, the association analysis itself is unable to present the complex relationships among many keywords in some adjacent research areas. To overcome this limitation, we propose the hybrid approach for establishing association network among keywords used in research papers. The keyword association network can be established by the following phases : i) a set of keywords specified in a certain paper are regarded as co-purchased items, ii) perform association analysis for the keywords and extract frequent patterns of keywords that satisfy predefined thresholds of confidence, support, and lift, and iii) schematize the frequent keyword patterns as a network to show the core keywords of each research area and connecting keywords among two or more research areas. To estimate the practical application of our approach, we performed a simple experiment with 600 keywords. The keywords are extracted from 131 research papers published in five prominent Korean journals in 2009. In the experiment, we used the SAS Enterprise Miner for association analysis and the R software for social network analysis. As the final outcome, we presented a network diagram and a cluster dendrogram for the keyword association network. We summarized the results in Section 4 of this paper. The main contribution of our proposed approach can be found in the following aspects : i) the keyword network can provide an initial roadmap of a research area to researchers who are novice in the domain, ii) a researcher can grasp the distribution of many keywords neighboring to a certain keyword, and iii) researchers can get some idea for converging different research areas by observing connecting keywords in the keyword association network. Further studies should include the following. First, the current version of our approach does not implement a standard meta-dictionary. For practical use, homonyms, synonyms, and multilingual problems should be resolved with a standard meta-dictionary. Additionally, more clear guidelines for clustering research areas and defining core and connecting keywords should be provided. Finally, intensive experiments not only on Korean research papers but also on international papers should be performed in further studies.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.151-166
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• 2020

A recommender system is a system that recommends products or services that best meet the preferences of each customer using statistical or machine learning techniques. Collaborative filtering (CF) is the most commonly used algorithm for implementing recommender systems. However, in most cases, it only uses purchase history or customer ratings, even though customers provide numerous other data that are available. E-commerce customers frequently use a search function to find the products in which they are interested among the vast array of products offered. Such search keyword data may be a very useful information source for modeling customer preferences. However, it is rarely used as a source of information for recommendation systems. In this paper, we propose a novel hybrid CF model based on the Doc2Vec algorithm using search keywords and purchase history data of online shopping mall customers. To validate the applicability of the proposed model, we empirically tested its performance using real-world online shopping mall data from Korea. As the number of recommended products increases, the recommendation performance of the proposed CF (or, hybrid CF based on the customer's search keywords) is improved. On the other hand, the performance of a conventional CF gradually decreased as the number of recommended products increased. As a result, we found that using search keyword data effectively represents customer preferences and might contribute to an improvement in conventional CF recommender systems.

• Journal of Information Management
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• v.40 no.3
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• pp.79-97
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• 2009

Thanks to current development of many search engines and web technologies, a new semantic searching technology appears, featuring giving a relevant meaning to the keyword beyond the previous keyword search service. On the wave of advance of various search engines, the enhancement of OASIS offered by KIOM is needed as well. To do this, KIOM examined demographic and sociological analysis on their position, status, and career, the convenience of OASIS, and the value of papers offered in OASIS from members who have ever used it. Furthermore, the importance of each area involved in oriental medicine is also examined in terms of a new direction for OASIS improvement. Based on the result of the user survey, it turned out that not only an automatic search system that can find meaning of chinese character-centered key words but also a Authority-system which can distinguish homonym beyond simple keyword search system should be introduced quickly. Also, we reached the conclusion that it is necessary to interconnect a citation index information on references with laboratory information of the agencies concerned and interconnect major web sites around the world by using Open API. OASIS is the only domestic web site for offering papers that cover oriental medicine. Therefore, if requirements about the site in oriental medical circles are analyzed sufficiently and the problems of its information search system are improved, OASIS is expected to play a critical role in the development of oriental medicine.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.4
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• pp.811-819
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• 2012

In this paper, we design searchable image encryption system to provide the privacy and authentication on streaming media based on cloud computing. The searchable encryption system is the matrix of searchable image encryption system by extending the streaming search from text search, the search of the streaming service is available, and supports personal privacy and authentication using encryption/decryption and CBIR technique. In simple simulation of post-cut and image keyword creation, we can verify the possibilities of the searchable image encryption system based on streaming service.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.21 no.4
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• pp.205-215
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• 2010

This study has extracted the basic component of the Library Course Pages through case studies of the Library Course Pages Service, and examined the staus quo of the Open Course Ware(OCW) for the sharing of the course materials. The study has also designed and established a ontology-based retrieval system model that is capable of semantic-based retrieval of the course materials in colleges. A comparison between and analysis of the past keyword search results was conducted to evaluate the model. Through evaluation, the study concluded that the ontology-based system was more effective than the keyword search method in both retrieval result and material sharing between the institutions.

• The Transactions of the Korea Information Processing Society
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• v.7 no.12
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• pp.3855-3865
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• 2000

The automatic indexing is a compulsory part for the text retrieval system. However it is impossible to rank the appropriate texts at top. Furthermore, it is more difficult to prevent to rank the inappropriate texts having homonyms at top by only the automatic indexing. In this paper, we proposed the two-level retrieval system to enhance the retrieval efficiency, in which Automatic Keyword Network (AKN) is used at the second-level process. The firsHevel search is carried out with an inverted index file generated by the automatic indexing. On the other hand the second-level search exploits AKN based on the degree of asslxiation between terms. We have developed several formulas for rearranging the rank of texts at second-level search, and evaluated the performance of the effects of them on resolving the word sense ambiguities.

• 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 Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.126-136
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• 2020

Recently, unmanned aerial vehicles (UAV, Drone) are highly regarded for their potential in the agricultural field, and research and development are actively conducted for various purposes. Therefore, in this study, to present a framework for tracking research trends in UAV use in the agricultural field, we secured a keyword search strategy and analyzed social network, a methodology used to analyze recent research trends or technological trends as an analysis model applied. This study consists of three stages. As a first step in data acquisition, search terms and search formulas were developed for experts in accordance with the Keyword Search Strategy. Data collection was conducted based on completed search terms and search expressions. As a second step, frequency analysis was conducted by country, academic field, and journal based on the number of thesis presentations. Finally, social network analysis was performed. The analysis used the open source programming language 'Python'. Thanks to the efficiency and convenience of unmanned aerial vehicles, this field is growing rapidly and China and the United States are leading global research. Korea ranked 18th, and bold investment in this field is needed to advance agriculture. The results of this study's analysis could be used as important information in government policy making.