• Asia Marketing Journal
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• v.26 no.1
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• pp.1-10
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• 2024

This study explores incomplete decision-making dynamics on reward-based crowdfunding platforms, focusing on temporal and social factors influencing backers' decisions. Utilizing the temporal aspect (i.e., pledging campaign phase) and social aspect (i.e., current pledged amount ratio) as stimuli within the stimulus-organism-response framework, our findings reveal that nearly 50.9% of respondents change their initial decisions, highlighting widespread incomplete information processing. Backers are more prone to altering decisions under heightened time pressure and display herding behaviors. Furthermore, backers exhibit an increased likelihood of changing decisions under heightened time pressure, coupled with a greater chance that the pledged goal amount will not be achieved. The study discusses theoretical and practical implications.

• Journal of the Korean Data and Information Science Society
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• v.7 no.2
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• pp.289-294
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• 1996

This paper considers the limit of the ratio of two incomplete beta functions $I_{x}(p+s,q+r)\;to\;I_{x}(p,q)\;as\;p+q{\rightarrow}{\infty}$. The results show that the limits depend on r,s,x and the limit of p/(p+q).

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.281-287
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• 1999

Decision class analysis (DCA) is viewed as a classification problem where a set of input data (situation-specific knowledge) and output data(a topological leveled influence diagram (ID)) is given. Situation-specific knowledge is usually given from a decision maker (DM) with the help of domain expert(s). But it is not easy for the DM to know the situation-specific knowledge of decision problem exactly. This paper presents a methodology for sensitivity analysis of DCA under incomplete information. The purpose of sensitivity analysis in DCA is to identify the effects of incomplete situation-specific frames whose uncertainty affects the importance of each variable in the resulting model. For such a purpose, our suggested methodology consists of two procedures: generative procedure and adaptive procedure. An interactive procedure is also suggested based the sensitivity analysis to build a well-formed ID. These procedures are formally explained and illustrated with a raw material purchasing problem.

• The Journal of Information Technology and Database
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• v.3 no.2
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• pp.75-96
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• 1996

This study is intended to compare the effectiveness of the neural network inductive learning model with a vector space model in information retrieval. As a result, searches responding to incomplete queries in the neural network inductive learning model produced a higher precision and recall as compared with searches responding to complete queries in the vector space model. The results show that the hybrid methodology of integrating an inductive learning technique with the neural network model can help solve information retrieval problems that are the results of inconsistent indexing and incomplete queries--problems that have plagued information retrieval effectiveness.

• International Journal of Advanced Culture Technology
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• v.7 no.3
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• pp.92-96
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• 2019

This study analyzes the problems of fire qualification information websites and job search websites due to incomplete information in the job search process and suggests an improvement plan. It has been confirmed that the main reason for the cost of job searching is incomplete information required for a job search and job search through existing analysis. As a result, it is suggested to construct a smooth information system for economic entities and to provide easy access to information by mitigating the incompleteness of information. Based on this, analysis of the problems of Korean qualifications in the firefighting realm reveals that there is a qualification holder information and a job information site, and a qualification holder management system is established but only information of either qualification acquisition information or employment information is provided. In addition, it is easy to access information through a qualification acquisition information and employment information site via the Internet, but there are inconveniences that qualification acquisition information and employment information are dualized. In order to improve this, it is necessary to build a new customized integrated qualification management system that covers existing Q-net qualification acquisition information and worknet employment information.

• The KIPS Transactions:PartC
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• v.18C no.3
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• pp.127-134
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• 2011

Malicious botnet has been used for more malicious activities, such as DDoS attacks, sending spam messages, steal personal information, etc. To prevent this, many studies have been preceded. But malicious botnets have evolved and evaded detection systems. In particular, HTTP GET Request attack that exploits the vulnerability of the application layer is used. ALAB of ALADDIN proposed by ETRI is DDoS attack detection system that HTTP GET, Incomplete GET request flooding attack detection algorithm is applied. In this paper, we extend Incomplete GET detection algorithm of ALAB and derive the optimal configuration parameters to verify the validity of the algorithm ALAB by the study of the normal and attack packets.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.4
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• pp.855-861
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• 2017

Gordon & Loeb[1] suggested that the optimal level of investment decision of an enterprise is the point that the marginal benefit(MB) of information security investment is equal to the marginal cost(MC). However, many companies suffering from information security incidents are not aware of the fact that they are experiencing information security accidents and can not measure how much they are affected. In this paper, I propose a model of information security investment decision making under the incomplete information situation by modifying the Gordon & Loeb[1] model and compare the differences in investment level. Under the incomplete information situation the expected return from the information security investment tends to be lower than that of actual information security investment, and the level of investment is also less. This shows that if a third party such as the government gives accurate information such as the rate of incidents of information security accidents and the amount of damages, companies can expand their investment in information security.

• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.7-13
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• 2021

This paper introduces an algorithm that compensates for missing values after converting them into a format that can represent the probability for incomplete data including missing values in training data. In the previous method using this data conversion, incomplete data was processed by allocating missing values with an equal probability that missing variables can have. This method applied to many problems and obtained good results, but it was pointed out that there is a loss of information in that all information remaining in the missing variable is ignored and a new value is assigned. On the other hand, in the new proposed method, only complete information not including missing values is input into the well-known classification algorithm (C4.5), and the decision tree is constructed during learning. Then, the probability of the missing value is obtained from this decision tree and assigned as an estimated value of the missing variable. That is, some lost information is recovered using a lot of information that has not been lost from incomplete learning data.

• Journal of Intelligence and Information Systems
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• v.9 no.2
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• pp.51-63
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• 2003

Collaborative filtering is one of the methodologies that are most widely used for recommendation system. It is based on a data matrix of each customer's preferences of products. There could be a lot of missing values in such preference data matrix. This incomplete data is one of the reasons to deteriorate the accuracy of recommendation system. There are several treatments to deal with the incomplete data problem such as case deletion and single imputation. Those approaches are simple and easy to implement but they may provide biased results. Multiple imputation method imputes m values for each missing value. It overcomes flaws of single imputation approaches through considering the uncertainty of missing values. The objective of this paper is to suggest multiple imputation-based collaborative filtering approach for recommendation system to improve the accuracy in prediction performance. The experimental works show that the proposed approach provides better performance than the traditional Collaborative filtering approach, especially in case that there are a lot of missing values in dataset used for recommendation system.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.27-32
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• 2014

Two-dimensional hybrid codewords are generated by using each row of identity matrix for spatial encoding and nonideal symmetric balance incomplete block design(BIBD) code for spectral encoding. This spatial/spectral optical code-division multiple-access (OCDMA) network uses single-balanced detectors to abstract the desired information bits and to eliminate the multiple-access interference(MAI). Analytical results show that the number of simultaneous users increases significantly by using the proposed hybrid codes.