1,752 research outputs found
The Unbalanced Linguistic Aggregation Operator in Group Decision Making
Published version of an article in the journal: Mathematical problems in engineering. Also available from Hindawi: http://dx.doi.org/10.1155/2012/619162Many linguistic aggregation methods have been proposed and applied in the linguistic decision-
making problems. In practice, experts need to assess a number of values in a side of reference
domain higher than in the other one; that is, experts use unbalanced linguistic values to express
their evaluation for problems. In this paper, we propose a new linguistic aggregation operator to
deal with unbalanced linguistic values in group decision making, we adopt 2-tuple representation
model of linguistic values and linguistic hierarchies to express unbalanced linguistic values, and
moreover,we present the unbalanced linguistic ordered weighted geometric operator to aggregate
unbalanced linguistic evaluation values; a comparison example is given to show the advantage of
ourmethod
Distributed Linguistic Representations in Decision Making: Taxonomy, Key Elements and Applications, and Challenges in Data Science and Explainable Artificial Intelligence
Distributed linguistic representations are powerful tools for modelling the uncertainty and complexity of preference information in linguistic decision making. To provide a comprehensive perspective on the development of distributed linguistic representations in decision making, we present the taxonomy of existing distributed linguistic representations. Then, we review the key elements and applications of distributed linguistic information processing in decision making, including the distance measurement, aggregation methods, distributed linguistic preference relations, and distributed linguistic multiple attribute decision making models. Next, we provide a discussion on ongoing challenges and future research directions from the perspective of data science and explainable artificial intelligence.National Natural Science Foundation of China (NSFC) 71971039
71421001,71910107002,71771037,71874023
71871149Sichuan University sksyl201705
2018hhs-5
Dynamic adaptation of user profiles in recommender systems
In a period of time in which the content available through the Internet
increases exponentially and is more easily accessible every day, techniques
for aiding the selection and extraction of important and personalised
information are of vital importance. Recommender Systems (RS) appear as
a tool to help the user in a decision making process by evaluating a set of
objects or alternatives and aiding the user at choosing which one/s of them
suits better his/her interests or preferences. Those preferences need to be
accurate enough to produce adequate recommendations and should be
updated if the user changes his/her likes or if they are incorrect or
incomplete. In this work an adequate model for managing user preferences
in a multi-attribute (numerical and categorical) environment is presented to
aid at providing recommendations in those kinds of contexts. The
evaluation process of the recommender system designed is supported by a
new aggregation operator (Unbalanced LOWA) that enables the
combination of the information that defines an alternative into a single
value, which then is used to rank the whole set of alternatives. After the
recommendation has been made, learning processes have been designed to
evaluate the user interaction with the system to find out, in a dynamic and
unsupervised way, if the user profile in which the recommendation process
relies on needs to be updated with new preferences. The work detailed in
this document also includes extensive evaluation and testing of all the
elements that take part in the recommendation and learning processes
The induced 2-tuple linguistic generalized OWA operator and its application in linguistic decision making
We present the induced 2-tuple linguistic generalized ordered weighted averaging (2-TILGOWA) operator. This new aggregation operator extends previous approaches by using generalized means, order-inducing variables in the reordering of the arguments and linguistic information represented with the 2-tuple linguistic approach. Its main advantage is that it includes a wide range of linguistic aggregation operators. Thus, its analyses can be seen from different perspectives and we obtain a much more complete picture of the situation considered and are able to select the alternative that best fits with with our interests or beliefs. We further generalize the operator by using quasi-arithmetic means, and obtain the Quasi-2-TILOWA operator. We conclude this paper by analysing the applicability of this new approach in a decision-making problem concerning product management.linguistic decision making, linguistic generalized mean, 2-tuple linguistic owa operator, 2-tuple linguistic aggregation operator
Personalized individual semantics in Computing with Words for supporting linguistic Group Decision Making. An Application on Consensus reaching
Yucheng Dong would like to acknowledge the financial support of grants
(Nos. 71171160, 71571124) from NSF of China, and a grant (No.xq15b01)
from SSEM key research center at Sichuan province. Enrique Herrera-Viedma
and Luis Mart´ınez would like to acknowledge the FEDER funds under Grant
TIN2013-40658-P and TIN2015-66524-P respectivelyIn group decision making (GDM) dealing with Computing with Words (CW)
has been highlighted the importance of the statement, words mean different
things for different people, because of its influence in the final decision. Different proposals that either grouping such different meanings (uncertainty)
to provide one representation for all people or use multi-granular linguistic
term sets with the semantics of each granularity, have been developed and
applied in the specialized literature. Despite these models are quite useful
they do not model individually yet the different meanings of each person
when he/she elicits linguistic information. Hence, in this paper a personalized individual semantics (PIS) model is proposed to personalize individual
semantics by means of an interval numerical scale and the 2-tuple linguistic
model. Specifically, a consistency-driven optimization-based model to obtain
and represent the PIS is introduced. A new CW framework based on the
2-tuple linguistic model is then defined, such a CW framework allows us to deal with PIS to facilitate CW keeping the idea that words mean different
things to different people. In order to justify the feasibility and validity of the
PIS model, it is applied to solve linguistic GDM problems with a consensus
reaching process.National Natural Science Foundation of China
71171160
71571124Sichuan University
skqy201606European Union (EU)
TIN2013-40658-P
TIN2015-66524-
Induced hesitant 2-tuple linguistic aggregation operators with application in group decision making
In this article, hesitant 2-tuple linguistic arguments are used to evaluate the group decision making problems which have inter dependent or inter active attributes. Operational laws are developed for hesitant 2-tuple linguistic elements and based on these operational laws hesitant 2- tuple weighted averaging operator and generalized hesitant 2- tuple averaging operator are proposed. Combining Choquet integral with hesitant 2-tuple linguistic information, some new aggregation operators are defined, including the hesitant 2-tuple correlated averaging operator, the hesitant 2-tuple correlated geometric operator and the generalized hesitant 2-tuple correlated averaging operator. These proposed operators successfully manage the correlations among the elements. After investigating the properties of these operators, a multiple attribute decision making method based on these operators, is suggested. Finally, an example is given to illustrate the practicality and feasibility of proposed method
Generalized Hamacher aggregation operators for intuitionistic uncertain linguistic sets: Multiple attribute group decision making methods
© 2019 by the authors. In this paper, we consider multiple attribute group decision making (MAGDM) problems in which the attribute values take the form of intuitionistic uncertain linguistic variables. Based on Hamacher operations, we developed several Hamacher aggregation operators, which generalize the arithmetic aggregation operators and geometric aggregation operators, and extend the algebraic aggregation operators and Einstein aggregation operators. A number of special cases for the two operators with respect to the parameters are discussed in detail. Also, we developed an intuitionistic uncertain linguistic generalized Hamacher hybrid weighted average operator to reflect the importance degrees of both the given intuitionistic uncertain linguistic variables and their ordered positions. Based on the generalized Hamacher aggregation operator, we propose a method for MAGDM for intuitionistic uncertain linguistic sets. Finally, a numerical example and comparative analysis with related decision making methods are provided to illustrate the practicality and feasibility of the proposed method
Pythagorean 2-tuple linguistic power aggregation operators in multiple attribute decision making
In this paper, we investigate the multiple attribute decision making
problems with Pythagorean 2-tuple linguistic information.
Then, we utilize power average and power geometric operations
to develop some Pythagorean 2-tuple linguistic power aggregation
operators: Pythagorean 2-tuple linguistic power weighted
average (P2TLPWA) operator, Pythagorean 2-tuple linguistic power
weighted geometric (P2TLPWG) operator, Pythagorean 2-tuple linguistic
power ordered weighted average (P2TLPOWA) operator,
Pythagorean 2-tuple linguistic power ordered weighted geometric
(P2TLPOWG) operator, Pythagorean 2-tuple linguistic power
hybrid average (P2TLPHA) operator and Pythagorean 2-tuple linguistic
power hybrid geometric (P2TLPHG) operator. The prominent
characteristic of these proposed operators are studied. Then,
we have utilized these operators to develop some approaches to
solve the Pythagorean 2-tuple linguistic multiple attribute decision
making problems. Finally, a practical example for enterprise
resource planning (ERP) system selection is given to verify the
developed approach and to demonstrate its practicality and
effectiveness
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