Examinando por Autor "Herrera, Francisco"
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Ítem A Group Decision Making Model Dealing with Comparative Linguistic Expressions based on Hesitant Fuzzy Linguistic Term Sets(Elsevier, 2013-08) Rodríguez, Rosa M.; Martínez, Luis; Herrera, FranciscoThe complexity and impact of many real world decision making problems lead to the necessity of considering multiple points of view, building group decision making problems in which a group of experts provide their preferences to achieve a solution. In such complex problems uncertainty is often present and although the use of linguistic information has provided successful results in managing it, these are sometimes limited because the linguistic models use single-valued and predefined terms that restrict the richness of freely eliciting the preferences of the experts. Usually, experts may doubt between different linguistic terms and require richer expressions to express their knowledge more accurately. However, linguistic group decision making approaches do not provide any model to make more flexible the elicitation of linguistic preferences in such hesitant situations. In this paper is proposed a new linguistic group decision model that facilitates the elicitation of flexible and rich linguistic expressions, in particular through the use of comparative linguistic expressions, close to human beings’ cognitive models for expressing linguistic preferences based on hesitant fuzzy linguistic term sets and context-free grammars. This model defines the group decision process and the necessary operators and tools to manage such linguistic expressions.Ítem Consensus Building With Individual Consistency Control in Group Decision Making(IEEE, 2018-07) Li, CongCong; Rodriguez, Rosa M.; Martinez, Luis; Dong, Yucheng; Herrera, FranciscoThe individual consistency and the consensus degree are two basic measures to conduct group decision making with reciprocal preference relations. The existing frameworks to manage individual consistency and consensus degree have been investigated intensively and follow a common resolution scheme composed by the two phases: the consistency improving process, and the consensus reaching process. But in these frameworks, the individual consistency will often be destroyed in the consensus reaching process, leading to repeat the consistency improving process, which is time consuming. In order to avoid repeating the consistency improving process, a consensus reaching process with individual consistency control is proposed in this paper. This novel consensus approach is based on the design of an optimization-based consensus rule, which can be used to determine the adjustment range of each preference value guaranteeing the individual consistency across the process. Finally, theoretical and numerical analysis are both used to justify the validity of our proposal.Ítem Consistency of hesitant fuzzy linguistic preference relations: An interval consistency index(Elsevier, 2018-03) Li, CongCong; Rodriguez, Rosa M.; Herrera, Francisco; Martínez, Luis; Dong, YuchengThe study of hesitant consistency is very important in decision-making with hesitant fuzzy linguistic preference relations (HFLPRs), and generally the normalization method is used as a tool to measure the consistency degree of a HFLPR. In this paper we propose a new hes- itant consistency measure, called interval consistency index, to estimate the consistency range of a HFLPR. The underlying idea of the interval consistency index consists of measur- ing the worst consistency index and the best consistency index of a HFLPR. Furthermore, by comparative study, a connection is shown between the interval consistency index and the normalization method, demonstrating that the normalization method should be con- sidered as an approximate average consistency index of a HFLPR.Ítem Deriving the priority weights from incomplete hesitant fuzzy preference relations in group decision making(Elsevier, 2016-05) Xu, Yejun; Chen, Lei; Rodríguez, Rosa M.; Herrera, Francisco; Wang, HuiminThe concept of hesitant fuzzy preference relation (HFPR) has been recently introduced to allow the de- cision makers (DMs) to provide several possible preference values over two alternatives. This paper in- troduces a new type of fuzzy preference structure, called incomplete HFPRs, to describe hesitant and incomplete evaluation information in the group decision making (GDM) process. Furthermore, we define the concept of multiplicative consistency incomplete HFPR and additive consistency incomplete HFPR, and then propose two goal programming models to derive the priority weights from an incomplete HFPR based on multiplicative consistency and additive consistency respectively. These two goal programming models are also extended to obtain the collective priority vector of several incomplete HFPRs. Finally, a numerical example and a practical application in strategy initiatives are provided to illustrate the validity and applicability of the proposed models.Ítem E2SAM: Evolutionary ensemble of sentiment analysis methods for domain adaptation(2019-04) López, Miguel; Valdivia, Ana; Martínez Cámara, Eugenio; Luzón, M. Victoria; Herrera, FranciscoCurrently, a plethora of industrial and academic sentiment analysis methods for classifying the opinion polarity of a text are available and ready to use. However, each of those methods have their strengths and weaknesses, due mainly to the approach followed in their design (supervised/unsupervised) or the domain of text used in their development. The weaknesses are usually related to the capacity of generalisation of machine learning algorithms, and the lexical coverage of linguistic resources. Those issues are two of the main causes of one of the challenges of Sentiment Analysis, namely the domain adaptation problem. We argue that the right ensemble of a set of heterogeneous Sentiment Analysis Methods will lessen the domain adaptation problem. Thus, we propose a new methodology for optimising the contribution of a set of off-the-shelf Sentiment Analysis Methods in an ensemble classifier depending on the domain of the input text. The results clearly show that our claim holds.Ítem Hesitant Fuzzy Sets: State of the Art and Future Directions(Wiley, 2014-04) Rodríguez, Rosa M.; Martínez, Luis; Torra, Vicenç; Xu, Zeshui; Herrera, FranciscoThe necessity of dealing with uncertainty in real world problems has been a long-term research challenge that has originated different methodologies and theories. Fuzzy sets along with their extensions, such as type-2 fuzzy sets, interval-valued fuzzy sets, and Atanassov’s intuitionistic fuzzy sets, have provided a wide range of tools that are able to deal with uncertainty in different types of problems. Recently, a new extension of fuzzy sets so-called hesitant fuzzy sets has been introduced to deal with hesitant situations, which were not well managed by the previous tools. Hesitant fuzzy sets have attracted very quickly the attention of many researchers that have proposed diverse extensions, several types of operators to compute with such types of information, and eventually some applications have been developed. Because of such a growth, this paper presents an overview on hesitant fuzzy sets with the aim of providing a clear perspective on the different concepts, tools and trends related to this extension of fuzzy sets.Ítem Personalized individual semantics based on consistency in hesitant linguistic group decision making with comparative linguistic expressions(Elsevier, 2018-04) Li, CongCong; Rodriguez, Rosa M.; Martinez, Luis; Dong, Yucheng; Herrera, FranciscoIn decision making problems, decision makers may prefer to use more flexible linguistic expressions in- stead of using only one linguistic term to express their preferences. The recent proposals of hesitant fuzzy linguistic terms sets (HFLTSs) are developed to support the elicitation of comparative linguistic expressions in hesitant decision situations. In group decision making (GDM), the statement that words mean different things for different people has been highlighted and it is natural that a word should be defined by individual semantics described by different numerical values. Considering this statement in hesitant linguistic decision making, the aim of this paper is to personalize individual semantics in the hesitant GDM with comparative linguistic expressions to show the individual difference in understanding the meaning of words. In our study, the personalized individual semantics are carried out by the fuzzy envelopes of HFLTSs based on the personalized numerical scales of linguistic term set.