• 정보관리연구
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• 제40권1호
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• pp.29-46
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• 2009

학위논문은 중요한 학술자원이나, 출판 및 유통되지 않는 특성으로 인해 검색, 접근, 입수, 활용 면에서 어려움이 있다. 이 연구는 5개 기관 및 6개 서비스에서 제공하는 학위논문의 이용현황을 분석하여 전반적인 학위논문 제공서비스의 개선방안을 제시하는 데 그 목적이 있다. 이를 위해서 학위논문을 실제로 이용한 경험이 있는 이용자를 대상으로 설문조사를 실시하였다. 6개의 학위논문 제공서비스 중에서 국회도서관과 RISS 서비스가 높은 인지도와 사용률을 나타냈으며, 이용자들은 제목과 저자 이외에도 키워드, 원문제공 여부, 학과, 초록, 목차 등의 정보원을 중요한 검색항목으로 사용했다. 이용자들이 가장 중요하게 여기는 것은 학위논문의 원문제공 여부이며, 원문을 제공하지 않을 경우에는 제공처에 대한 링크 또는 안내를 필요로 하였다. 따라서 학위논문 이용 활성화를 위해서는 제공서비스의 홍보와 다양한 서지정보가 필요하며, 무엇보다도 중요한 것은 학위논문의 원문을 제공하는 것이다.

• Asia pacific journal of information systems
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• 제26권4호
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• pp.577-592
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• 2016

The proliferation of mobile applications and the unique characteristics of the mobile environment have attracted significant research interest in understanding customers' purchasing behaviors in mobile commerce. In this study, we extend customer value theory by combining the predictors of product performance with customer value framework to investigate how in-store information creates value for customers and influences mobile application downloads. Using a data set collected from the Google Application Store, we find that customers value both text and non-text information when they make downloading decisions. We apply latent semantic analysis techniques to analyze customer reviews and product descriptions in the mobile application store and determine the embedded valuable information. Results show that, for mobile applications, price, number of raters, and helpful information in customer reviews and product descriptions significantly affect the number of downloads. Conversely, average rating does not work in the mobile environment. This study contributes to the literature by revealing the role of in-store information in mobile application downloads and by providing application developers with useful guidance about increasing application downloads by improving in-store information management.

• 한국산업정보학회논문지
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• 제22권5호
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• pp.9-15
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• 2017

디지털 시대에 인터넷에서 사용되는 모든 데이터는 디지털화되어 통신 네트워크를 통해 송신 및 수신된다. 따라서 디지털 데이터가 불법적인 사용자에 의해 변조되고 조작될 수 있기 때문에 기밀성과 무결성을 갖춘 암호화된 데이터를 전송하는 것이 중요하다. 스테가노그래피는 암호화 기법과 혼합되어 기밀성과 무결성을 함께 보장하기 위한 효율적인 방법이다. 커버 매체에 삽입되는 위치와 변화하는 어절 형태를 기반으로 비밀 메시지를 삽입하는 한글 텍스트 스테가노그래피 방법을 제안한다. 한글 텍스트 스테가노그래피에서 3.35%의 삽입용량과 0.4%의 파일 크기 변화를 고려할 때 실험결과는 Jaro_score 값이 0.946으로 유지할 필요가 있다는 것을 보여준다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권9호
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• pp.4568-4584
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• 2016

Steganography based on text generation has become a hot research topic in recent years. However, current text-generation methods which generate texts of normal style have either semantic or syntactic flaws. Note that texts of special genre, such as poem, have much simpler language model, less grammar rules, and lower demand for naturalness. Motivated by this observation, in this paper, we propose a text steganography that utilizes Markov chain model to generate Ci-poetry, a classic Chinese poem style. Since all Ci poems have fixed tone patterns, the generation process is to select proper words based on a chosen tone pattern. Markov chain model can obtain a state transfer matrix which simulates the language model of Ci-poetry by learning from a given corpus. To begin with an initial word, we can hide secret message when we use the state transfer matrix to choose a next word, and iterating until the end of the whole Ci poem. Extensive experiments are conducted and both machine and human evaluation results show that our method can generate Ci-poetry with higher naturalness than former researches and achieve competitive embedding rate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권3호
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• pp.560-574
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• 2011

In this paper, we propose a hybrid method of Machine Learning (ML) algorithm and a rule-based algorithm to implement a lightweight Named Entity (NE) extraction system for Korean SMS text. NE extraction from Korean SMS text is a challenging theme due to the resource limitation on a mobile phone, corruptions in input text, need for extension to include personal information stored in a mobile phone, and sparsity of training data. The proposed hybrid method retaining the advantages of statistical ML and rule-based algorithms provides fully-automated procedures for the combination of ML approaches and their correction rules using a threshold-based soft decision function. The proposed method is applied to Korean SMS texts to extract person's names as well as location names which are key information in personal appointment management system. Our proposed system achieved 80.53% in F-measure in this domain, superior to those of the conventional ML approaches.

• Journal of the Korean Data and Information Science Society
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• 제25권6호
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• pp.1419-1429
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• 2014

본 논문에서는 1977년 미국 국립기술표준원이 FIPS (연방정보처리기준; federal information processing standard) 46으로 공표한 암호화 표준인 현대 대칭키 블록 암호 DES (data encryption standard)의 암호화 전 과정에 대하여 엑셀 매크로 기능을 활용하여 암호화와 복호화에 사용할 수 있는 매크로를 개발하였다. 평문과 암호문과의 관계를 숨기는 확산과 암호문과 암호 키 사이의 관계를 숨기는 혼돈을 반복하는 라운드는 DES 구조의 핵심이다. 평문을 암호화 하는 DES 구조를 살펴보고 엑셀 매크로기능을 이용하여 암호화를 완성하는 매크로의 구현을 제안하고 개발된 매크로의 정확성과 활용성을 서술하였다.

• 방송공학회논문지
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• 제26권5호
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• pp.592-598
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• 2021

현 이동통신 시스템은 재난경보 방송을 위하여 CBS 프로토콜을 이용한다. 그러나 CBS 프로토콜 표준은 제한된 텍스트 문자의 전송만을 규정하고 있다. 따라서 국내 문자에 익숙하지 않은 외국인 등은 수신된 메시지를 충분히 이해하기 어려운 단점이 있다. 또한, 현 CBS는 메시지의 글자수 제한으로 자세한 정보를 전송하기 어려운 한계를 가진다. 이러한 어려움을 극복하기 위하여 본 논문에서는 CBS 재난문자 전송시 단말기에서 이미지 정보 와 URL을 표출하는 기법을 제안한다. 이 기법은 5G 이동통신을 위한 CBS의 메시지 구조를 이용한다. 이 메시지 구조를 이용할 경우 CBS 프로토콜은 문자 코딩방식에 관계없이 단말기에서 이미지 정보와 URL을 표출할 수 있음을 보인다.

• Journal of Information Science Theory and Practice
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• 제7권1호
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• pp.52-71
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• 2019

An insider threat is a threat that comes from people within the organization being attacked. It can be described as a function of the motivation, opportunity, and capability of the insider. Compared to managing the dimensions of opportunity and capability, assessing one's motivation in committing malicious acts poses more challenges to organizations because it usually involves a more obtrusive process of psychological examination. The existing body of research in psycholinguistics suggests that automated text analysis of electronic communications can be an alternative for predicting and detecting insider threat through unobtrusive behavior monitoring. However, a major challenge in employing this approach is that it is difficult to minimize the risk of missing any potential threat while maintaining an acceptable false alarm rate. To deal with the trade-off between the risk of missed catches and the false alarm rate, we propose a unified psycholinguistic framework that consolidates multiple text analyzers to carry out sentiment analysis, emotion analysis, and topic modeling on electronic communications for unobtrusive psychological assessment. The user scenarios presented in this paper demonstrated how the trade-off issue can be attenuated with different text analyzers working collaboratively to provide more comprehensive summaries of users' psychological states.

• 한국정보시스템학회지:정보시스템연구
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• 제30권2호
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• pp.189-214
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• 2021

Purpose This paper aims to effectively utilize user-generated content (UGC) and analyze the market structure of a relatively new market which lacks rich user review information. Specifically, we propose a domain-specific text mining tool for the domestic craft beer market and visualize the market structure by incorporating how individual beer products are positioned in the perceptual map of consumers. Design/methodology/approach We collect user review information from Naver blogs, and extract words that describe beers. We identify semantic relationships between beer products through text mining, and then depending on these semantic relationships, construct a graph representing the market structure of the domestic craft beer market based on the consumer's perceptual map. Findings First, beer products produced in the same brewery are perceived as very similar to consumers. Second, only two products, 'Heukdang Milky Stout' and 'Gompyo', was noticeably distinguishable from other products. Third, even though 'Gyeongbokgung' is from a different brewery, it is located very close to the products of 'Jeju Beer' brewery such as 'Jeju Baeknokdam Ale' and 'Seongsan Ilchulbong Ale', which suggests the influence of 'landmark series.' We successfully show that our methodology effectively describes the market structure of the craft beer market.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권4호
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• pp.1409-1425
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• 2021

In wide-ranging information society, fast and easy access to information in language of one's choice is indispensable, which may be provided by using various multilingual Natural Language Processing (NLP) applications. Natural language text contains references among different language elements, called anaphoric links. Resolving anaphoric links is a key problem in NLP. Anaphora resolution is an essential part of NLP applications. Anaphoric links need to be properly interpreted for clear understanding of natural languages. For this purpose, a mechanism is desirable for the identification and resolution of these naturally occurring anaphoric links. In this paper, a framework based on Hobbs syntactic approach and a system developed by Lappin & Leass is proposed for resolution of reflexive anaphoric links, present in Urdu text documents. Generally, anaphora resolution process takes three main steps: identification of the anaphor, location of the candidate antecedent(s) and selection of the appropriate antecedent. The proposed framework is based on exploring the syntactic structure of reflexive anaphors to find out various features for constructing heuristic rules to develop an algorithm for resolving these anaphoric references. System takes Urdu text containing reflexive anaphors as input, and outputs Urdu text with resolved reflexive anaphoric links. Despite having scarcity of Urdu resources, our results are encouraging. The proposed framework can be utilized in multilingual NLP (m-NLP) applications.