Ranking fuzzy numbers plays a main role in many applied models inreal world and in particular decision-making procedures. In manyproposed methods by other researchers may exist some shortcoming.The most commonly used approaches for ranking fuzzy numbers isbased on defuzzification method. Many ranking fuzzy numberscannot discriminate between two symmetric fuzzy numbers withidentical core. In 200...

In this paper, we propose a new ranking method inspired from previous results on the diffusion approach to solve linear equation. We describe new mathematical equations corresponding to this method and show through experimental results the potential computational gain. This ranking method is also compared to the well known PageRank model. Keywords-Large sparse matrix, Iteration, Fixed point, Pa...

A ranking method assigns to every directed graph a (weak) ordering of the nodes. In this paper, we axiomatize the ranking method that ranks the nodes according to their outdegree. This method generalizes the ranking by Copeland score for tournaments as characterized in Rubinstein (SIAM J. Appl. Math. 38 (1980) 108–111). c © 2003 Elsevier B.V. All rights reserved.

the recent years have witnessed an increasing attention to the methods of multiple attribute decision making in solving the problems of the real world due to their shorter time of calculation and easy application. one of these methods is the ‘permutation method’ which has a strong logic in connection with ranking issues, but when the number of alternatives increases, solving problems through th...

In this paper, we present a framework for improving the ranking function training and the re-ranking process for web search personalization. Our method is based on utilizing clickthrough data from several users in order to create multiple ranking functions that correspond to different topic areas. Those ranking functions are combined each time a user poses a new query in order to produce a new ...

in many applications, ranking of decision making units (dmus) is a problematic technical task procedure to decision makers in data envelopment analysis (dea), especially when there are extremely efficient dmus. in such cases, many dea models may usually get the same efficiency score for different dmus. hence, there is a growing interest in ranking techniques yet. the purpose of this paper is ra...

This paper presents a novel ranking method for complex semantic relationship (semantic association) search based on user preferences. Our method employs a learning-to-rank algorithm to capture each user's preferences. Using this, it automatically constructs a personalized ranking function for the user. The ranking function is then used to sort the results of each subsequent query by the user. Q...

This paper describes the participation of the SNUMedinfo team at the TREC Clinical Decision Support track 2014. This task is about medical casebased retrieval. Case description is used as query text. Per each query, one of three categories (Diagnosis, Test and Treatment) is designated as target information need. Firstly, we used external tagged knowledge-based query expansion method for the rel...