• Journal of the Korean Society for information Management
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• v.27 no.3
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• pp.227-239
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• 2010

Opinion retrieval is to retrieve items which are relevant to the user information need topically and include opinion about the topic. This paper aims to find a method to represent user information need for effective opinion retrieval and to analyze the combination methods for opinion features through various experiments. The experiments are carried out in the inference network framework using the Blogs06 collection and 100 TREC test topics. The results show that our suggested representation method based on hidden 'opinion' concept is effective, and the compact model with very small opinion lexicon shows the comparable performance to the previous model on the same test data set.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.3
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• pp.197-214
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• 1996

Financial analysis of stock data usually involves extensive computation of large amount of time series data sets. To handle the large size of the data sets and complexity of the analyses, database management systems have been increasingly adaopted for efficient management of stock data. Specially, relational database management system is employed more widely due to its simplistic data management approach. However, the normalized two-dimensional tables and the structured query language of the relational system turn out to be less effective than expected in accommodating time series stock data as well as the various computational operations. This paper explores a new data management approach to stock data management on the basis of an object-oriented database management system (ODBMS), and proposes a data model supporting times series data storage and incorporating a set of financial analysis functions. In terms of functional stock data analysis, it specially focuses on a primitive set of operations such as variance of stock data. In accomplishing this, we first point out the problems of a relational approach to the management of stock data and show the strength of the ODBMS. We secondly propose an object model delineating the structural relationships among objects used in the stock data management and behavioral operations involved in the financial analysis. A prototype system is developed using a commercial ODBMS.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.3 no.4
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• pp.319-324
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• 2002

The Integration of agent technology and security technology is needed to many application areas like electronic commerce. This paper suggests a model of extended multi-agent engine which supports privacy, integrity, authentication and non-repudiation on agent communication. Each agent which is developed with the agent engine is composed of agent engine layer and agent application layer. We describe and use the concepts self-to-self messages, secure communication channel, and distinction of KQML messages in agent application layer and messages in agent engine layer. The suggested agent engine provides an agent communication language which is extended to enable secure communication between agents without any modifications or restrictions to content layer and message layer of KQML. Also, in the model of our multi-agent engine, secure communication is expressed and processed transparently on the agent communication language.

• Korean Journal of Cognitive Science
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• v.6 no.3
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• pp.65-81
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• 1995

Compound nouns as a composition of multiple nouns exhibit diverse occurence patterns in the texts and have varying degree of meaning coherence.The problem of compound nouns in information retrieval is to find a method to represent and identify the compositive patterns of each words.This paper explains how the cooccurrence patterns are related with the meaning of each compound noun and the information of such relations that can be mechanically acquired from texts is used in ranking the candidated documents for a given query.The main theme of the paper is that compound nouns can be categorized according to their occurrence patterns of simple nouns and these occurrence patterns can be formalized by statistical analysis without large dictionary or complex compositive rules.Our suggested model achieved about 7.75% improvement over the best precision of the other methods at each recall measurements on Korean test collection.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.6116-6132
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• 2017

The proxy re-encryption allows an intermediate proxy to convert a ciphertext for Alice into a ciphertext for Bob without seeing the original message and leaking out relevant information. Unlike many prior identity based proxy re-encryption schemes which are based on the number theoretic assumptions such as large integer factorization and discrete logarithm problem. In this paper, we first propose a novel identity based proxy re-encryption scheme which is based on the hardness of standard Learning With Error(LWE) problem and is CPA secure in the standard model. This scheme can be reduced to the worst-case lattice hard problem that is able to resist attacks from quantum algorithm. The key step in our construction is that the challenger how to answer the private query under a known trapdoor matrix. Our scheme enjoys properties of the non-interactivity, unidirectionality, anonymous and so on. In this paper, we utilize primitives include G-trapdoor for lattice and sample algorithms to realize simple and efficient re-encryption.

• Journal of Korean Academy of Nursing Administration
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• v.8 no.3
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• pp.411-430
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• 2002

Purpose : This study was to develop Nursing Process Model of abdominal surgery patient using nursing diagnoses of NANDA, Nursing Interventions Classification(NIC), and Nursing Outcomes Classification(NOC). Method : The data in database were collected from nursing records in sixty patients with abdominal surgery admitted in a university hospital and open questionnaires of thirteen nurses. Systematic nursing process resulting from each nursing diagnoses, most common, was developed by the statistical analysis through database query from clinical database of abdominal surgery patients. Result : 51 nursing diagnoses were identified in abdominal surgery patients. The most commonly occurred nursing diagnoses were Pain, Risk for Infection, Sleep Pattern Disturbance, Hyperthermia, Altered Nutrition: Less Than Body Requirements in order. The linkage lists of NANDA to NIC and NANDA to NOC, and the nursing activities according to nursing diagnoses of abdominal surgery patients were identified in unit. Conclusion : Nursing Process of abdominal surgery patients was comprised of core nursing diagnoses, core nursing interventions, core nursing outcomes which provides the most reliable data in unit and could make nurses facilitate nursing process easily without full consideration of knowledge about nursing language classification system. Therefore, it could support nurses' decision making and recording of nursing process especially in the computerized patient record system if unit nursing process model using standardized nursing language system which contains of their own core nursing process data was developed.

• Journal of Information Science Theory and Practice
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• v.7 no.3
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• pp.21-30
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• 2019

Information about the formation and filling (in 2014 to 2016) of a terminological dictionary on electronics and radioengineering and collective work (in 2017 to 2018) with a data bank "TERMIN" is presented in this article. In purpose of creating an instrument of navigating the modern scientific-technical space a net of terms with set semantic links is described. This set is based on the analysis of terms' definitions (each term is checked for inclusion in the definitions of all other terms; the definitions were borrowed from reputable reference editions: encyclopedias, dictionaries, reference books). The created model of a system that consists of different information sources, in which it (information) is indexed by the terminology of Russian State Rubricator of Scientific and Technical Information rubrics and/or keywords, is described. There is an access for the search in all these sources in the system. Searching inquiries are referred to in the language of these rubrics or formulated by arbitrary terms. The system is to refer to information sources and give out relevant information. In accordance with this model, semantic links of various types, which allow expanding a search at different modalities of query, should be set among data bank terms. Obtained links will have to increase semantic matching, i.e., they can provide actual understanding of the meaning of the information that is being sought.

• ETRI Journal
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• v.43 no.1
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• pp.40-52
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• 2021

DNS (Domain Name System) tunnels almost obscure the true network activities of users, which makes it challenging for the gateway or censorship equipment to identify malicious or unpermitted network behaviors. An efficient way to address this problem is to conduct a temporal-spatial analysis on the tunnel traffic. Nevertheless, current studies on this topic limit the DNS tunnel to those with a single protocol, whereas more than one protocol may be used simultaneously. In this paper, we concentrate on the refined identification of two protocols mixed in a DNS tunnel. A feature set is first derived from DNS query and response flows, which is incorporated with deep neural networks to construct a regression model. We benchmark the proposed method with captured DNS tunnel traffic, the experimental results show that the proposed scheme can achieve identification accuracy of more than 90%. To the best of our knowledge, the proposed scheme is the first to estimate the ratios of two mixed protocols in DNS tunnels.

• Journal of Information Technology Services
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• v.22 no.1
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• pp.29-42
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• 2023

Amid the global movement to harness individual data and boost the data economy, MyData services that utilize personal data are being implemented in earnest in the financial sector in Korea due to the government's active encouragement policy. To this end, MyData service providers must have a service system for business operators that collects and efficiently loads personal information scattered in various financial institutions with individual consent, and comprehensively analyzes and provides it. The system must not only have strict security management capabilities, but also be built in a flexible form that takes into account future data scalability and additional services. In this paper, it has been proposed to be implemented the essential functions that MyData service system must have and the core functions that can manage the entire data life cycle from data collection, distribution to disposal in the form of a platform. In addition, the strengths of the platform structure were reviewed, and the effectiveness of the platform model was examined upon application.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.61-63
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• 2021

Machine learning model gained the popularity in recent years as multi-national companies have incorporated machine learning in their services. Such service is called machine learning as a service (MLaSS). Such services are provided to users based on charge-per-query which triggers the motivations for adversaries to steal the trained victim model to reduce the cost of using the service. Therefore, it is important for companies that provide MLaSS to protect their intellectual property (IP) against adversaries. It has been arms race between the attack and defence in a context of the privacy of machine learning models. In this paper, we provide a comprehensive study of recent development in protecting privacy of machine learning models.