• Asia pacific journal of information systems
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• v.13 no.1
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• pp.103-118
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• 2003

Software project planning is usually represented by a project activity network that is composed of stages of tasks to be done and precedence restrictions among them. The project network is very complex and its construction requires a vast amount of field knowledge and experience. So this study proposes a case-based reasoning approach that can generate the project network automatically based on the past cases and modification knowledge. For the case indexing, we have adopted 17 factors, each with a few alternative values. A special structure of this problem is that the modification effort can be identified by each factor independently. Thus it is manageable to identify 85 primitive modification actions(add and delete activities) and estimate its modification efforts in advance. A specific case requires a combination of primitive modifications. Based on the modification effort knowledge, we have adopted the Least Modification approach as a metric of similarity between a new project and past cases. Using the Least Modification approach and modification knowledge base, we can automatically generate the project network. To validate the performance of Least Modification approach, we have compared its performance with an ordinary minimal distance approach for 21 test cases. The experiment showed that the Least Modification approach could reduce the modification effort significantly.

• Annual Conference on Human and Language Technology
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• 2004.10d
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• pp.159-166
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• 2004

본 논문에서는 질의응답 시스템에서 질문의 주제와 개념적으로 일치하는 단락으로부터 정보를 추출할 경우에 보다 정확한 정답을 추출할 수 있다는 가정 하에 문장 주제를 활용한 의미적 단락 생성 및 검색 기법을 제안한다. 문장주제란 백과사전 문서 집합에서 공통으로 기술하는 내용이나 자주 언급하고 있는 사건 혹은 개념들의 집합을 의미하는 것으로, 주제별로 응집된 문장들로 재구성된 단락을 의미적 단락이라고 정의한다. 제안된 방법의 성능을 평가하기 위해 의미적 단락의 신뢰도를 파악하고, 백과사전 본문을 3문장 단위로 잘라서 고정길이 단락을 만든 후 의미적 단락의 검색결과와 비교하였다. 평가척도로는 TREC의 역순위평균(MRR : Mean Reciprocal Rank)과 상위 5개 단락 안에 정답유무를 측정하는 사용자 정답만족도를 사용하였다. ETRI 평가셋을 대상으로 한 실험 결과, 주제를 이용한 의미적 단락 검색 성능이 고정길이 단락 검색보다 우수함을 알 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3230-3255
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• 2022

Causality mining in NLP is a significant area of interest, which benefits in many daily life applications, including decision making, business risk management, question answering, future event prediction, scenario generation, and information retrieval. Mining those causalities was a challenging and open problem for the prior non-statistical and statistical techniques using web sources that required hand-crafted linguistics patterns for feature engineering, which were subject to domain knowledge and required much human effort. Those studies overlooked implicit, ambiguous, and heterogeneous causality and focused on explicit causality mining. In contrast to statistical and non-statistical approaches, we present Bidirectional Encoder Representations from Transformers (BERT) integrated with Multi-level Feature Networks (MFN) for causality recognition, called BERT+MFN for causality recognition in noisy and informal web datasets without human-designed features. In our model, MFN consists of a three-column knowledge-oriented network (TC-KN), bi-LSTM, and Relation Network (RN) that mine causality information at the segment level. BERT captures semantic features at the word level. We perform experiments on Alternative Lexicalization (AltLexes) datasets. The experimental outcomes show that our model outperforms baseline causality and text mining techniques.

• Journal of Digital Contents Society
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• v.2 no.2
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• pp.103-115
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• 2001

This paper proposes the two algorithms which generate a minimal decision rule and approximate inference operation, adapted the rough set and the factor space theory in fuzzy knowledge base. The generation of the minimal decision rule is executed by the data classification technique and reduct applying the correlation analysis and the Bayesian theorem related attribute factors. To retrieve the specific object, this paper proposes the approximate inference method defining the membership function and the combination operation of t-norm in the minimal knowledge base composed of decision rule. We compare the suggested algorithms with the other retrieval theories such as possibility theory, factor space theory, Max-Min, Max-product and Max-average composition operations through the simulation generating the object numbers and the attribute values randomly as the memory size grows. With the result of the comparison, we prove that the suggested algorithm technique is faster than the previous ones to retrieve the object in access time.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.730-733
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• 2004

Recently XML (eXtensible Markup Language) is becoming the standard for exchanging the documents on the web. And as the amount of information is increasing because of the development of the technique in the Internet, semantic web is becoming to appear for more exact result of information retrieval than the existing one on the web. Ontology which is the basis of the semantic web provides the basic knowledge system to express a particular knowledge. So it can show the exact result of the information retrieval. Ontology defines the particular concepts and the relationships between the concepts about specific domain and it has the hierarchy similar to the taxonomy. In this paper, we propose the generation of semi-automatic ontology based on XML documents that are interesting to many researchers as the means of knowledge expression. To construct the ontology in a particular domain, we suggest the algorithm to determine the domain. So we determined that the domain of ontology is to extract the information of movie on the web. And we used the generalized association rules, one of data mining methods, to generate the ontology, using the tag and contents of XML documents. And XTM (XML Topic Maps), ISO Standard, is used to construct the ontology as an ontology language. The advantage of this method is that because we construct the ontology based on the terms frequently used documents related in the domain, it is useful to query and retrieve the related domain.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.21 no.4
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• pp.300-304
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• 2008

A novel characterization method was investigated to estimate the trap generation during the program /erase cycles in nand flash memory cell. Utilizing Fowler-Nordheim tunneling current, floating gate potential and oxide electric field, we established a quantitative model which allows the knowledge of threshold voltage (Vth) as a function of either program or erase operation time. Based on our model, the derived results proved that interface trap density (Nit) term is only included in the program operation equation, while both Nit and oxide trap density (Not) term are included in the erase operation equation. The effectiveness of our model was tested using 50 nm nand flash memory cell with floating gate type. Nit and Not were extracted through the analysis of Program/Erase speed with respect to the endurance cycle. Trap generation and cycle numbers showed the power dependency. Finally, with the measurement of the experiment concerning the variation of cell Vth with respect to program/erase cycles, we obtained the novel quantitative model which shows similar results of relationship between experimental values and extracted ones.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.10a
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• pp.403-409
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• 2003

The finite element method is one of the most widely used method of structural analysis that has wide applications in diverse fields of engineering and science. The method has been proven effective and reliable in many practical problems. One of the reasons for the methods' popularity is its ease of use, but still the user has to input the finite element mesh which affects the accuracy of the results. The knowledge required to form an effective mesh for a given problem is somewhat complex and for sometime there has been research effort to automate the generation of the mesh and this is called the adaptive mesh generation scheme. A good adaptive mesh scheme seemed to require an accurate assessment of error and generally this requires some additional computation. This paper looks into the possibility of generating adaptive meshes based on representative strain values in each finite element method. The proposed adaptive scheme does not require additional computations other that looking up the data values already computed as finite element analysis results and simple manipulations of these data. Two plane stress problems, a plate with a hole and a deep beam with a concentrated load at the end are considered to show the progress of the improved generation of adaptive meshes using the scheme.

• The Journal of Economics, Marketing and Management
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• v.11 no.4
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• pp.41-52
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• 2023

Purpose: The study examines the effect of TechTubers' unboxing videos on consumer buying behavior by highlighting the role of product touch, visual and verbal sensory cues. The study integrates the vicarious touch and the dual coding theory to analyze the Smartphone purchase behavior of Generation Z. Research design, data and methodology: The study collected data from 349 respondents who were viewers of YouTube unboxing videos. A structured questionnaire using a 5-point Likert scale was employed as a survey instrument. Convenience sampling technique was utilized to select the samples. The data were analyzed using structural equation modeling (SEM). Results: Results reveal that vicarious touch and verbal description have a statistically significant positive effect on Generation Z's purchase intention of Smartphone. Moreover, purchase intention positively affects Generation Z's actual purchase behavior of Smartphone. However, the visual images did not significantly affect purchase intention. Conclusions: The study offers significant theoretical and practical implications. The study adds new knowledge to the extant literary field by highlighting the impact of digital product presentation in the form of Unboxing videos on purchase intention for technology products. Moreover, the study suggests content sponsorship and advertising opportunities for marketers in collaboration with the TechTubers on YouTube unboxing video platform.

• School Mathematics
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• v.15 no.1
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• pp.201-219
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• 2013

The purpose of this study was to analyse the belief about mathematics teaching of elementary preservice teachers and mathematics teachers. This study involved 100 respondents from the preservice teachers and 114 respondents from the mathematics teachers. The instruments used in this study consist 15 items of mathematical knowledges and 19 items of mathematical activities. The finding showed that preservice teachers emphasized the conceptual knowledge, whereas mathematics teachers emphasized the procedural knowledge in the mathematical knowledges. And preservice teachers emphasized the knowledge representation, knowledge generation, knowledge deliberation, knowledge communication, whereas mathematics teachers emphasized the use of knowledge(syntax) in the mathematical activities. Finally, even though two groups showed the significant difference in some items, preservice teachers and mathematics teachers emphasized the various mathematical knowledges and mathematical activities.

• Journal of the Korean Society for Library and Information Science
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• v.37 no.2
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• pp.343-364
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• 2003

The importance of Knowledge Management (KM) can be easily recognized in many diverse aspects of the theory studies and in KM's efforts to help implement the government's policy to innovate corporation management. The core of KM is to improve the circulation of knowledge by generation, accumulation, sharing, utilization and acquisition by learning. The improvement of knowledge circulation would result in high quality and quantity of intellectual assets in corporations and make decision-making more efficient. This, too, is the operational philosophy of the special libraries. The primary objective of this study is to promote KM by presenting KM methodology and by explaining a theoretical background and cases, based on the existing special libraries. I cite an example of a case wherein merging intellectual assets and human resources activated the company culture. The reference service system, which is the core of the special library, was used in this merging.