• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1454-1466
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• 2016

This paper implements an estimated ranking algorithm of closeness centrality measures in large-scale workflow-supported social networks. The traditional ranking algorithms for large-scale networks have suffered from the time complexity problem. The larger the network size is, the bigger dramatically the computation time becomes. To solve the problem on calculating ranks of closeness centrality measures in a large-scale workflow-supported social network, this paper takes an estimation-driven ranking approach, in which the ranking algorithm calculates the estimated closeness centrality measures by applying the approximation method, and then pick out a candidate set of top k actors based on their ranks of the estimated closeness centrality measures. Ultimately, the exact ranking result of the candidate set is obtained by the pure closeness centrality algorithm [1] computing the exact closeness centrality measures. The ranking algorithm of the estimation-driven ranking approach especially developed for workflow-supported social networks is named as RankCCWSSN (Rank Closeness Centrality Workflow-supported Social Network) algorithm. Based upon the algorithm, we conduct the performance evaluations, and compare the outcomes with the results from the pure algorithm. Additionally we extend the algorithm so as to be applied into weighted workflow-supported social networks that are represented by weighted matrices. After all, we confirmed that the time efficiency of the estimation-driven approach with our ranking algorithm is much higher (about 50% improvement) than the traditional approach.

• Journal of Korea Multimedia Society
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• v.16 no.11
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• pp.1305-1314
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• 2013

The existing tag based system deducts a retrieval result with low accuracy through the usage of a single tag matching by using tags tagged in contents. And the system doesn't provide effectively contents related information which the tags have, as the users place tags on contents without considering the priority and associative relation between tags. For a solve of above problems, this paper suggests a tag ranking system which extracts semantic similarity between tags and re-ranks the tags tagged in contents. In order to evaluate the performance of suggested system, this paper experiments and compares the ranking result of this paper's tag ranking system with the result of baseline method using tags tagged in images and frequency method adapting tag co-appearance frequency.

• Knowledge Management Research
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• v.6 no.2
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• pp.105-118
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• 2005

The future will see all industries become technology-driven in the competitive global market place. Firms with deep technological roots and innovation strategies have some advantages. Business valuation of technology is critical to the future of firm's business. In this situation widely used scoring valuation is not enough to evaluate relative business competitiveness associated with technology and to assign its relative ranking category. Therefore, a more useful and comprehensive new valuation approach, which is called business composite index, is needed to complement and to enhance the existing scoring valuation approach. In this research, statistical factor analysis is applied to determine the common factors and to estimate associated weights. And business composite index, which is a kind of weighted scoring method, is derived based on the results of factor analysis. This research shows that business composite index is considered very useful to measure the business relative strength of individual technology and also to assign its relative ranking category instead of absolute ranking based on scoring valuation approach.

• Journal of Environmental Impact Assessment
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• v.6 no.1
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• pp.93-103
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• 1997

LHR(Landfill Site Hazard Ranking Model) was developed for ranking the relative hazard of landfill sites by using the method of value-structured approach. LHR consists of combining a multiattribute decision-making method with a Qualitative risk assessment approach. A pairwise com parisian method was applied to determine weights of landfill site factors related. To determine the hazard of landfill site, hydrogeological factors, waste characteristics factors and receptors factors were evaluated by LHR. LHR can help decision-makers prioritization of remediation of landfill sites through the relatively convenient and concise evaluation method of landfill site features related. LHR focuses mainly on pathways of groundwater and surfacewater for evaluating landfill hazard to receptors including humans. To validiate the applicability of LHR, Nanjido Landfill site, Metropolitan Landfill site, and Hwasung Landfill site were evaluated.

• The Journal of the Korea Contents Association
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• v.12 no.8
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• pp.388-398
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• 2012

In this study, Entropy method and PROMETHEE(Preference Ranking organization METHod for Enrichment Evaluations) which is one of the multi criteria decision making methods are applied to estimate the relative inundation risk ranking of the urban sewer systems. Then, the evaluation factors were selected considering two main items to estimate the inundation risk using Entropy and PROMETHEE. In the first item considering topographical and environmental factor, average elevation, average slope, width of area, population, density of conduit were selected as the detailed factors of first item which have influence of the overflow occurrence and damage scale in urban sewer system. And, the relative reliability of sewer network was considered as the second item which can quantify the inundation appearance. Then, the reliability is estimated considering the number of overflow nodes and overflow volume simultaneously. Therefore, the suggested inundation risk evaluation method can be used as the evaluation index for sewer networks and contribute to decision making for the sewer rehabilitation policy.

• Environmental Analysis Health and Toxicology
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• v.24 no.2
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• pp.95-105
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• 2009

Chemical Ranking and Scoring (CRS) system is a useful tool to screen priority chemicals of large body of substances. The relative ranking of chemicals based on CRS system has served as a decision-making support tools. Exposure potential and toxicity are significant parameters in CRS system, and there are differences in evaluating those parameters in each CRS system. In this study, the parameters of exposure potential, human toxicity, and ecotoxicity were extensively compared. In addition the scoring methods in each parameter were analyzed. The CRS systems considered in this study include the CHEMS-1 (Chemical Hazard Evaluation for Management Strategies), SCRAM (Scoring and Ranking Assessment Model), EURAM (European Union Risk Ranking Method), ARET (Accelerated Reduction/Elimination of Toxics), and CRS-Korea. An comparative analysis of the several CRS systems is presented based on their assessment parameters and scoring methods.

• Nuclear Engineering and Technology
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• v.52 no.12
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• pp.2821-2835
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• 2020

The phenomenon identification and ranking table (PIRT) is an important basis in the nuclear power plant (NPP) thermal-hydraulic analysis. This study focuses on the importance ranking of the input parameters when lacking the PIRT, and the target scenario is the small break loss of coolant accident (SBLOCA) in a pressurized water reactor (PWR) CPR1000. A total of 54 input parameters which might have influence on the figure of merit (FOM) were identified, and the sensitivity measure of each input on the FOM was calculated through an optimized moment-independent global sensitivity analysis method. The importance ranking orders of the parameters were transformed into the Savage scores, and the parameters were categorized based on the Savage scores. A parameter importance ranking table for the SBLOCA scenario of the CPR1000 reactor was obtained, and the influences of some important parameters at different break sizes and different accident stages were analyzed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.145-148
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• 2002

Type-1 fuzzy value is used to show the uncertainty in a given value. But there exist many situations that it needs to be extended to type-2 fuzzy value because it is difficult to determine the crisp membership function itself. Intrinsically type-2 fuzzy values are more expressive and powerful than type-1 fuzzy values, but, at the same time, more difficult to be compared or ranked . In this paper, a ranking method for type-2 fuzzy values is proposed. It is based on the satisfaction function which shows the possibility that one type-2 fuzzy value is greater than the other type-2 fuzzy value Some properties of the proposed method are also analyzed .

• The KIPS Transactions:PartD
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• v.19D no.1
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• pp.15-20
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• 2012

In this paper, to solve a vested interests of old papers in scientific literature ranking, we propose novel method that considers not only the current citations from other published papers but also the latent citations of papers to be published in the future. Furthermore, the method also considers the relevance of contents in the citing and cited papers. Finally, we verify the superiority of our proposed method through extensive experiments.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.5
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• pp.427-435
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• 2005

With the accumulation of protein and its related data on the Internet, many domain based computational techniques to predict protein interactions have been developed. However, most of the techniques still have many limitations to be used in real fields. They usually suffer from a low accuracy problem in prediction and do not provide any interaction possibility ranking method for multiple protein pairs. In this paper, we reevaluate a domain combination based protein interaction prediction method and develop an interaction possibility ranking method for multiple protein pairs. Probability equations are devised and proposed in the framework of domain combination based protein interaction prediction method. Using the ranking method, one can discern which protein pair is more probable to interact with each other than other protein pairs in multiple protein pairs. In the validation of the ranking method, we revealed that there exist some correlations between the interacting probability and the precision of the prediction in case of the protein pair group having the matching PIP(Primary Interaction Probability) values in the interacting or non interacting PIP distributions.