• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.5
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• pp.843-850
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• 2006

The standardization on RDD and REL has been developed by MPEG. REL is a Right Expression Language and RDD is term dictionary which develop active application of REL. However, since REL documents could be oかy edited by user understanding MPEG-21's framework, much easier editing system is required. As well, REL Consumption System to process and analyze REL documents, the RDD interoperability system to interoperate REL and RDD are needed. In this paper, REL Editing System and REL Consumption System, RDD Web Services System were designed and implemented, REL Editing System to make REL document, REL Consumption System to process and analyze edited documents, RDD Web Services System to process rights inquiry base on the Web Services.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.155-166
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• 2018

These days, online media, such as blogospheres, online communities, and social networking sites, provides the uncountable user-generated content (UGC) to discover market intelligence and business insight with. The business has been interested in consumers, and constantly requires the approach to identify consumers' opinions and competitive advantage in the competing market. Analyzing consumers' opinion about oneself and rivals can help decision makers to gain in-depth and fine-grained understanding on the human and social behavioral dynamics underlying the competition. In order to accomplish the comparison study for rival products and companies, we attempted to do competitive analysis using text mining with online UGC for two popular and competing ramens, a market leader and a market follower, in the Korean instant noodle market. Furthermore, to overcome the lack of the Korean sentiment lexicon, we developed the domain specific sentiment dictionary of Korean texts. We gathered 19,386 pieces of blogs and forum messages, developed the Korean sentiment dictionary, and defined the taxonomy for categorization. In the context of our study, we employed sentiment analysis to present consumers' opinion and statistical analysis to demonstrate the differences between the competitors. Our results show that the sentiment portrayed by the text mining clearly differentiate the two rival noodles and convincingly confirm that one is a market leader and the other is a follower. In this regard, we expect this comparison can help business decision makers to understand rich in-depth competitive intelligence hidden in the social media.

• The KIPS Transactions:PartD
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• v.9D no.3
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• pp.427-434
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• 2002

For effective distributed software development, integrated information object management functions that manage the structures and relationships among information objects are most required. Presented in this paper is a managerial framework comprised of BOC (Bill Of Class) and part dictionary scheme for integrated information object management in distributed software development processes. Based on the proposed BOC and part dictionary scheme, an integrated information object management system is designed and implemented. As a result of this implementation work, the usefulness and benefit of proposed framework are also shown.

• Cross-Cultural Studies
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• v.31
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• pp.241-262
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• 2013

In this study, we select and analyze the slang that is represented in Elistratov's "Dictionary of Russian slang". Through the above analysis, some conclusions were drawn as follows: First, as a social and psychological phenomenon appears universal in all languages, the study of slang generates strict criteria for the analysis. Unlike literary language, listed in the dictionary slang expressions can become obsolete for their short period of usage by native speakers. Therefore, in the following research of the actual data, we have to validate words targeted for analysis. Second, as the result of the analysis it is metaphor for the most part studied rather than metonymy. The semantic derivations as a result of metonymy are used very frequently in real life. But in this study we mainly analyze words, therefore the number of words was less in metonymy than was expected. Third, the basic types of metaphor are appeared as similarity by form, function, and location, and there are varieties of intervening of subjectivity in similarity of emotional impression. Fourth, the metonymy is divided into three cases: the part meaning the whole, the whole meaning the part, and some thing meaning the reality of where it exists. Fifth, not only literary language, but also slang as the 'transitional process' is the most active way of development of new meanings, and there are two methods to transfer main meaning to second meaning.

• Journal of the Korea Society of Computer and Information
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• v.25 no.10
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• pp.87-94
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• 2020

Social reviews such as SNS feeds and blog articles have been widely used to extract keywords reflecting opinions and complaints from users' perspective, and often include proper nouns or new words reflecting recent trends. In general, these words are not included in a dictionary, so conventional morphological analyzers may not detect and extract those words from the reviews properly. In addition, due to their high processing time, it is inadequate to provide analysis results in a timely manner. This paper presents a method for efficient keyword extraction from social reviews based on the notion of cohesion scoring. Cohesion scores can be calculated based on word frequencies, so keyword extraction can be performed without a dictionary when using it. On the other hand, their accuracy can be degraded when input data with poor spacing is given. Regarding this, an algorithm is presented which improves the existing cohesion scoring mechanism using the structure of a word tree. Our experiment results show that it took only 0.008 seconds to extract keywords from 1,000 reviews in the proposed method while resulting in 15.5% error ratio which is better than the existing morphological analyzers.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.6
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• pp.544-550
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• 2015

The opinion mining technique which analogize significant information from SNS message is increasingly important because opinions communicated through SNS are increasing. This paper propose SEIAS(SNS Emotional Information Analysis Strategy) based on opinion mining that analogize emotional information from SNS setting a different weight according to position of antonym and adverb. Firstly, the proposed SEIAS constructs a emotion dictionary for opinion mining analysis, Secondly, it collects SNS data on real time, compare it with emotion dictionary and calculates opinion value of SNS data. Specially, it increases the precision of opinion analysis result compared to the existing SO-PMI because it sets up the different value according to the position of antonym and adverb when it calculates the opinion value of data.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.2
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• pp.124-133
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• 2009

CANopen which is one of the in-vehicle network (IVN) protocols is adopted to solve the hardware dependency problem of the CAN-based application. CANopen makes different CAN devices interoperable each others. By the advantage of the device profiling concept, it can make the period of developing CAN-based application system shorten. The utilization of CANopen network must be reduced to improve the communication performance (e.g. worst-case response time). For reducing network utilization, messages need to be packed as many as possible so that message frame overhead can be decreased. In this paper, we suggested a PDO packing mechanism using object dictionary (OD) and process data object (PDO) communication service in CANopen. Through experiments, the performance of the mechanism is evaluated with SAE benchmark. As a result, network utilization is decreased about 10% compared to the result of the previous works.

• The Journal of the Korea Contents Association
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• v.11 no.8
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• pp.247-259
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• 2011

It is necessary to collect, manage and standardize defense and technology terminologies which are used by defense-related agencies in the field of national defense science and technology. The standardization of terminology dictionary can eliminate confusion about terminology and increase accessibility for the terminology by offline and online services. This study focuses on building national defense science and technology terminologies, publishing dictionary including them, and improving information analysis in defense area. as well as take advantage of offline and online services for easy accessibility for the terminology. Based on the results of this study, the terminology data will be used as follows; 1) Defence science and technology terminology databases and its publication. 2) Information analysis in military fields. 3) Multilingual information analysis translated terms in the thesauri. 4) Verification on the consistency of information processing. 5) Language resources for terminology extraction.

• Electronics and Telecommunications Trends
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• v.33 no.1
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• pp.68-77
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• 2018

Data deduplication is a common used technology in backup systems and cloud storage to reduce storage costs and network traffic. To preserve data privacy from servers or malicious attackers, there has been a growing demand in recent years for individuals and companies to encrypt data and store encrypted data on a server. In this study, we introduce two cryptographic primitives, Convergent Encryption and Message-Locked Encryption, which enable deduplication of encrypted data between clients and a storage server. We analyze the security of these schemes in terms of dictionary and poison attacks. In addition, we introduce deduplication systems that can be implemented in real cloud storage, which is a practical application environment, and describes the proof of ownership on client-side deduplication.

• ETRI Journal
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• v.42 no.6
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• pp.815-826
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• 2020

We propose a two-dimensional (2D) scattering-center-extraction (SCE) method using sparse recovery based on the compressive-sensing theory, even with data missing from the received radar cross-section (RCS) dataset. First, using the proposed method, we generate a 2D grid via adaptive discretization that has a considerably smaller size than a fully sampled fine grid. Subsequently, the coarse estimation of 2D scattering centers is performed using both the method of iteratively reweighted least square and a general peak-finding algorithm. Finally, the fine estimation of 2D scattering centers is performed using the orthogonal matching pursuit (OMP) procedure from an adaptively sampled Fourier dictionary. The measured RCS data, as well as simulation data using the point-scatterer model, are used to evaluate the 2D SCE accuracy of the proposed method. The results indicate that the proposed method can achieve higher SCE accuracy for an incomplete RCS dataset with missing data than that achieved by the conventional OMP, basis pursuit, smoothed L0, and existing discrete spectral estimation techniques.