• Journal of Family Resource Management and Policy Review
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• v.10 no.3
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• pp.97-111
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• 2006

The objective of this research is to analyze how main social relation network of middle-aged women such as family, friends and neighbors, etc affects the preference for silver town. For this objective, structured questionnaires were distributed to 309 middle-aged women at the age of 40-59 years old living in Seoul and new cities of metropolitan area. Statistics such as ANOVA, Pearson Coefficient and Multiple Regression were adopted for statistical analysis. The main result of this research is as follows: First, housewives showed higher preference for silver town than people involved in other occupations. Second, though the relation of friends and neighbors among the social relation network of middle-aged women affected the preference for silver town, that of family did not affect significantly. The result of this research suggests that it is necessary to adopt policy considering the relation of friends and neighbors among the social relation network of middle-aged women so as to activate silver town.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.4
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• pp.832-839
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• 2009

In this paper, we introduce an design of fuzzy relation-based fuzzy neural networks with multi-output. Fuzzy relation-based fuzzy neural networks comprise the network structure generated by dividing the entire input space. The premise part of the fuzzy rules of the network reflects the relation of the division space for the entire input space and the consequent part of the fuzzy rules expresses three types of polynomial functions such as constant, linear, and modified quadratic. For the multi-output structure the neurons in the output layer were connected with connection weights. The learning of fuzzy neural networks is realized by adjusting connections of the neurons both in the consequent part of the fuzzy rules and in the output layer, and it follows a back-propagation algorithm. In addition, in order to optimize the network, the parameters of the network such as apexes of membership functions, learning rate and momentum coefficient are automatically optimized by using real-coded genetic algorithm. Two examples are included to evaluate the performance of the proposed network.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.819-822
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• 2012

This study is about social network services for tourism. In detail, the relationship among relation oriented activities, relation value, commitment and loyalty is analyzed in this paper.

• Journal of Korean Library and Information Science Society
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• v.39 no.2
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• pp.169-186
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• 2008

Social Network has been known as friendship basis human relation service in online network. But a broad sense of Social Network can be explained as a mechanism which makes web evolve to information-ecosystem by human relation and network data which has been generated by the mass of people's cooperation and interchange. Social Network has been expanding their domain from friendship basis relation service to broad social relationship focus of matter of concern. It has been applied to diverse domain. Library community begins to take an interest in Social Network concept to apply user's interchange for information. This paper considers the concept of Social network and it's appliance to a library service. For the more, suggest basic element for vitalizing library user's Social network.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.11C
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• pp.1158-1163
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• 2002

In this paper it is focused on the relation between CLR (Cell Loss Ratio) and blocking probability, GoS(Grade of Services) parameters in the wireless ATM (Asynchronous Transfer Mode) access network which consists of access node and wireless channel. Traffic model of wireless ATM access network is based on the cell scale, burst scale and call connection level. The CLR equation due to buffer overflow for wireless access node is derived for CBR (Constant Bit Rate) traffic. The CLR equation due to random bit errors and burst errors for wireless channel is derived. Using the CLR equation for both access node and wireless channel, the CLR equation of wireless ATM access network is derived. The relation between access network CLR and blocking probability is analyzed for CBR traffic.

• Journal of Information Technology Services
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• v.10 no.1
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• pp.47-64
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• 2011

In the IT(Information Technology) service, which supply the solutions related to business management and IT, network construction and application trends, the related service business are increasing according to the enlargement of project scope and the diversity of project types as the need of service customers. In this paper, I propose the significant effect factors on the network management of IT service firms. The key findings are from the analysis result about 94 IT service firms as follows. For implementation the high performance of network management in the IT service firms, the strategic elements in the process of network construction are more conceived highly than the basic element in them. Also the perspective of project objectives are considered than the nominal perspectives in the partner selection process. The competency of partner firms', the cooperation process between the partner firms', network relation operation management and network relation structure management are the significant effect factors of network management.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.3B
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• pp.233-242
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• 2011

This study quantified directional properties of channel network and hill slope for a river basin by applying the von Mises distribution, also examined the relation between them. Ultimately, it was examined that whether the directional properties of channel network and hill slope have a certain relation, which might be considered to the rainfall-runoff modeling. From the results derived by analyzing the Naesung stream basin, the von Mises distribution was found well to explain the directional characteristics of directional properties of channel network. There was a clear relation between directional properties of channel network and hill slope. The higher-order streams also showed very obvious modal characteristics. The results derived in this study could be helpful to estimate more quantitatively the difference in the runoff response with respect to the directional properties of channel network and hill slope.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.111-123
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• 2013

Semantic similarity/relatedness measure between two concepts plays an important role in research on system integration and database integration. Moreover, current research on keyword recommendation or tag clustering strongly depends on this kind of semantic measure. For this reason, many researchers in various fields including computer science and computational linguistics have tried to improve methods to calculating semantic similarity/relatedness measure. This study of similarity between concepts is meant to discover how a computational process can model the action of a human to determine the relationship between two concepts. Most research on calculating semantic similarity usually uses ready-made reference knowledge such as semantic network and dictionary to measure concept similarity. The topological method is used to calculated relatedness or similarity between concepts based on various forms of a semantic network including a hierarchical taxonomy. This approach assumes that the semantic network reflects the human knowledge well. The nodes in a network represent concepts, and way to measure the conceptual similarity between two nodes are also regarded as ways to determine the conceptual similarity of two words(i.e,. two nodes in a network). Topological method can be categorized as node-based or edge-based, which are also called the information content approach and the conceptual distance approach, respectively. The node-based approach is used to calculate similarity between concepts based on how much information the two concepts share in terms of a semantic network or taxonomy while edge-based approach estimates the distance between the nodes that correspond to the concepts being compared. Both of two approaches have assumed that the semantic network is static. That means topological approach has not considered the change of semantic relation between concepts in semantic network. However, as information communication technologies make advantage in sharing knowledge among people, semantic relation between concepts in semantic network may change. To explain the change in semantic relation, we adopt the cognitive semantics. The basic assumption of cognitive semantics is that humans judge the semantic relation based on their cognition and understanding of concepts. This cognition and understanding is called 'World Knowledge.' World knowledge can be categorized as personal knowledge and cultural knowledge. Personal knowledge means the knowledge from personal experience. Everyone can have different Personal Knowledge of same concept. Cultural Knowledge is the knowledge shared by people who are living in the same culture or using the same language. People in the same culture have common understanding of specific concepts. Cultural knowledge can be the starting point of discussion about the change of semantic relation. If the culture shared by people changes for some reasons, the human's cultural knowledge may also change. Today's society and culture are changing at a past face, and the change of cultural knowledge is not negligible issues in the research on semantic relationship between concepts. In this paper, we propose the future directions of research on semantic similarity. In other words, we discuss that how the research on semantic similarity can reflect the change of semantic relation caused by the change of cultural knowledge. We suggest three direction of future research on semantic similarity. First, the research should include the versioning and update methodology for semantic network. Second, semantic network which is dynamically generated can be used for the calculation of semantic similarity between concepts. If the researcher can develop the methodology to extract the semantic network from given knowledge base in real time, this approach can solve many problems related to the change of semantic relation. Third, the statistical approach based on corpus analysis can be an alternative for the method using semantic network. We believe that these proposed research direction can be the milestone of the research on semantic relation.

• Korean Parent-Child Health Journal
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• v.19 no.1
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• pp.25-32
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• 2016

Purpose: The purpose of this study was to use the social network analysis to verify the relationship between the interpersonal disposition and interactive characteristics of nursing college students. Five classes, a total of 117 nursing students were included in the study. Methods: The study interaction network centralization, density and in-degree & out-degree centrality were used as indicators for measuring students' study interaction. Also, the students' interpersonal disposition was measured using verified tool. Results: The results indicated that the ordinary type which gave and took the information generally showed the highest proportions in the study interaction network. Also, the empathic-acceptable tendency of social relation domain showed the highest proportions in the interpersonal disposition. Moreover, the students who play the isolate and the carrier role in the study interaction network had no relation with the expression tendency, and the transmitter role play students had no relation with the role tendency. Conclusion: Based on the results, the tutors should consider the students' interpersonal relationship disposition when implementing the instructional strategy in PBL curriculum.