• Title/Summary/Keyword: Ranking

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RDF 지식 베이스의 자원 중요도 계산 알고리즘에 대한 연구

  • No, Sang-Gyu;Park, Hyeon-Jeong;Park, Jin-Su
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2007.05a
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    • pp.123-137
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    • 2007
  • The information space of semantic web comprised of various resources, properties, and relationships is more complex than that of WWW comprised of just documents and hyperlinks. Therefore, ranking methods in the semantic web should be modified to reflect the complexity of the information space. In this paper we propose a method of ranking query results from RDF(Resource Description Framework) knowledge bases. The ranking criterion is the importance of a resource computed based on the link structure of the RDF graph. Our method is expected to solve a few problems in the prior research including the Tightly-Knit Community Effect. We illustrate our methods using examples and discuss directions for future research.

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AGGREGATION OPERATORS OF CUBIC PICTURE FUZZY QUANTITIES AND THEIR APPLICATION IN DECISION SUPPORT SYSTEMS

  • Ashraf, Shahzaib;Abdullah, Saleem;Mahmood, Tahir
    • Korean Journal of Mathematics
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    • v.28 no.2
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    • pp.343-359
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    • 2020
  • The paper aim is to resolve the issue of ranking to the fuzzy numbers in decision analysis, artificial intelligence and optimization. In the literature lot of ideologies have been established for ranking to the fuzzy numbers, that ideologies have some restrictions and limitations. In this paper, we proposed a method based on cubic picture fuzzy information's, for ranking to defeat the existing restrictions. Further introduced some cubic picture fuzzy algebraic and cubic picture fuzzy algebraic* aggregated operators for aggregated the information. Finally, a multi-attribute decision making problem is assumed as a practical application to establish the appropriateness and suitability of the proposed ranking approach.

Debris Flow Risk Evaluation and Ranking Method for Drainage Basin adjacent to Road (도로인근 유역의 토석류 위험평가 및 등급화 방안)

  • Kim, Kyung-Suk;Jang, Hyun-Ick
    • Proceedings of the Korean Geotechical Society Conference
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    • 2010.03a
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    • pp.279-290
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    • 2010
  • Technical countermeasures against debris flow should be established upon the risk level of the target location. Risk of debris flow should consider the hazard imposed by debris flow and vulnerability of the facilities to debris flow. In this research, we have defined the target location for risk evaluation and suggested scoring method of hazard of debris flow and vulnerability of road to debris flow. By defining risk rank into 6 categories in terms of possibility of damage during rainfall and using the risk scores of 46 debris flow cases, we have suggested risk ranking matrix. The method can be used in ranking the drainage basin adjacent to road by simply determining the hazard with vulnerability score and can be used for planning the debris flow countermeasures.

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Analysis of Korean Baduk rating system and dum (한국기원 기사 랭킹과 덤에 관한 분석)

  • Cho, Seonghun;Jang, Woncheol
    • The Korean Journal of Applied Statistics
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    • v.32 no.6
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    • pp.783-794
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    • 2019
  • The current ranking system of the Korean Baduk Association is based on the Elo rating system, which is widely used in the field of chess. Despite the 6.5 point dum (penalty) as compensation for playing as White, many Baduk players still prefer to playing as Black due to Black's higher winning percentage. In this paper, we present the ranking of Baduk players based on the Bradley-Terry model and address the advantage of playing as Black. We compare the ranking from our model with rankings from the Korean Baduk Association.

Contingency Severity Ranking Using Direct Method in Power Systems (전력계통에 있어서 직접법을 활용한 상정사고 위험순위 결정)

  • Lee, Sang-Keun
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.54 no.2
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    • pp.67-72
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    • 2005
  • This paper presents a method to select contingency ranking considering voltage security problems in power systems. Direct method which needs not the detailed knowledge of the post contingency voltage at each bus is used. Based on system operator's experience and knowledge, the membership functions for the MVAR mismatch and allowable voltage violation are justified describing linguistic representation with heuristic rules. Rule base is used for the computation of severity index for each contingency by fuzzy inference. Contingency ranking harmful to the system is formed by the index for security evaluation. Compared with 1P-1Q iteration, this algorithm using direct method and fuzzy inference shows higher computation speed and almost the same accuracy. The proposed method is applied to model system and KEPCO pratical system which consists of 311 buses and 609 lines to show its effectiveness.

Determining Contingency Ranking Using the Probabilistic Method of the Power System (확률적 방법을 이용한 전력계통의 상정사고 순위 결정)

  • Kim, Kyoung-Young;Lee, Seung-Hyuk;Kim, Jin-O;Kim, Tae-Kyun
    • Proceedings of the KIEE Conference
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    • 2003.07a
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    • pp.113-115
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    • 2003
  • The electric power industry throughout the world is undergoing considerable changes from the vertically integrated utility structure to the deregulated market. However, the deregulated electricity market is operated with respect to theory of economical efficiency, and therefore, the system operator requires data with fast contingency ranking for security of the bulk power system. This paper presents fast calculation method for determining contingency ranking using the weather dependant probabilistic risk index(PRI). The probabilistic risk index can be classified into normal weather and adverse weather. This paper proposes calculation method using the probabilistic risk index in determining contingency ranking requiring for security under the deregulated electricity market.

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A Method for Determining All the k Most Vital Arcs in the Maximum Flow Problem by Ranking of Cardinality Cuts (절단기수의 나열을 통한 최대유통문제에서 모든 k-치명호를 찾는 방법)

  • Ahn, Jae-Geun;Chung, Ho-Yeon;Park, Soon-Dal
    • Journal of Korean Institute of Industrial Engineers
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    • v.25 no.2
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    • pp.184-191
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    • 1999
  • The k most vital arcs (k-MVA) of a maximum flow problem is defined as those k arcs whose simultaneous removal from the network causes the greatest decrease in the throughput capability of the remaining system between a specified pair of nodes. In this study, we present a method for determining all the k-MVA in maximum flow problem using a minimal cardinality cut algorithm and k-th minimal cut ranking algorithm. For ranking cardinality cuts, we use Hamacher's ranking algorithm for cut capacity and by comparing present residual capacity of cardinality cut with expected residual capacity of next cardinality cut, we also present termination condition for this algorithm. While the previous methods cannot find all the alternatives for this problem, a method presented here has advantage of determining all the k-MVA.

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Causal model analysis between quantity and quality for deriving ranking model of Online reviews (온라인리뷰의 랭킹모델링을 위한 양과 질의 인과모형 분석)

  • Lee, Changyong;Kim, Keunhyung
    • The Journal of Information Systems
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    • v.28 no.1
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    • pp.1-16
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    • 2019
  • Purpose The purpose of this study is to analyze causal relationship between quantity and quality for deriving ranking model of Online reviews. Thus, we propose implications for deriving the ranking model for retrieving Online reviews more effectively. Design/methodology/approach We collected Online review from Tripadvisor web sites which might be a kind of world-famous tourism web sites. We transformed the natural text reviews to quantified data which consists of quantified positive opinions, quantified negative opinions, quantified modification opinions, reviews lengths and grade scores by using opinion mining technologies in R package. We executed corelation and regression analysis about the data. Findings According to the empirical analysis result, this study confirmed that the review length influenced positive opinion, negative opinion and modification opinion. We also confirmed that negative opinion and modification opinion influenced the grade score.

A Generic Multi-Level Algorithm for Prioritized Multi-Criteria Decision Making

  • G., AlShorbagy;Eslam, Hamouda;A.S., Abohamama
    • International Journal of Computer Science & Network Security
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    • v.23 no.1
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    • pp.25-32
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    • 2023
  • Decision-making refers to identifying the best alternative among a set of alternatives. When a set of criteria are involved, the decision-making is called multi-criteria decision-making (MCDM). In some cases, the involved criteria may be prioritized by the human decision-maker, which determines the importance degree for each criterion; hence, the decision-making becomes prioritized multi-criteria decision-making. The essence of prioritized MCDM is raking the different alternatives concerning the criteria and selecting best one(s) from the ranked list. This paper introduces a generic multi-level algorithm for ranking multiple alternatives in prioritized MCDM problems. The proposed algorithm is implemented by a decision support system for selecting the most critical short-road requests presented to the transportation ministry in the Kingdom of Saudi Arabia. The ranking results show that the proposed ranking algorithm achieves a good balance between the importance degrees determined by the human decision maker and the score value of the alternatives concerning the different criteria.

Analysis of Correlation between Real-time Sales Ranking and Information Provided by Mobile Movie Platform: Focus on Non-descriptive Information in Google Play Store's Best-selling Movies

  • Nam, Sangzo
    • Journal of Advanced Information Technology and Convergence
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    • v.9 no.2
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    • pp.41-54
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    • 2019
  • The cinema circuit is facing a digital, network, and mobile age, which expands non-theater accessibility to movies. Application platforms are situated as the most competitive business model that provide digital content such as games, music, books, and movies. Consumers can acquire content-related information not just offline, but online as well. Therefore, item information provided by application platforms is required. The information provided by application platforms consists of richly descriptive information such as storyline summary, consumer reviews, and related articles, while non-descriptive normative information covers data such as sales ranking, release date, genre, rental or purchase cost, domestic/foreign classification, consumer rating, number of consumer ratings, film rating, and so on. In this study, we surveyed and analyzed statistically the correlation between real-time sales ranking and other comparable non-descriptive information.