Nuria Agell

• PhD in Applied Mathematics
• Head of Department at ESADE Business School, Universitat Ramon Llull, Barcelona

Representing and interpreting human opinions within an unstructured framework is inherently complex. Hesitant fuzzy linguistic term sets offer a comprehensive context that facilitates a nuanced understanding of diverse perspectives. This study introduces a methodology that integrates sentiment analysis with hesitant fuzzy linguistic term sets to ef...

Managing a portfolio of digital products is challenging, particularly in a context of limited economic resources and workforce. Therefore, prioritization of activities and new developments is crucial. In Software Development environment, almost all well-known prioritization techniques are based on experts’ knowledge and opinion, leaving little room...

Representing and interpreting human opinions within an unstructured framework is inherently complex. Hesitant fuzzy linguistic term sets offer a comprehensive context that facilitates a nuanced understanding of diverse perspectives. This study introduces a methodology that integrates sentiment analysis with hesitant fuzzy linguistic term sets to ef...

According to the United Nations Food and Agriculture Organization (FAO) more than one third of the food produced globally is lost or wasted. This tremendous amount of food waste highlights the urgent need to investigate this phenomenon promptly with powerful methods in order to reduce it. In the present work, we consider a qualitative reasoning app...

In this study, we propose a methodology using hesitant fuzzy linguistic term sets to aggregate rating values. The main idea is to define an integrated methodology for collaborative platforms involving individuals that use the same set of linguistic terms with different semantics. The objective is to fuse the opinions of different profiles of review...

The 2022 Russian invasion of Ukraine sent shockwaves through Europe and led to rapid policy changes concomitant with variations in citizen perceptions. This article analyses how EU public opinion on security and defence matters has reacted to the war: what patterns of change and continuity can be detected, what differences are visible between Membe...

Interactions between the EU and IGOs ˗ such as joint statements, verbal public disagreements, formal cooperation agreements, and IGO dispute resolution involving the EU ˗ have increased in the past decades. We address the question What determines the EU’s interactions with formal IGOs? by carrying out a big data-based sentiment analysis of all news...

This paper considers the problem of finding suitable sites for wind farms in a region of Catalonia (Spain). The evaluation criteria are structured into a hierarchy that identifies several intermediate sub-goals dealing with different points of view. Therefore, the recent ELECTRE-III-H hierarchical multi-criteria analysis method is proposed as a goo...

This paper presents a multi-perceptual framework for multi-criteria group decision aiding based on unbalanced hesitant linguistic information. The concept of a perceptual map is introduced to break the uniformity among the set of basic labels considered in linguistic term sets. Projected perceptual maps are considered to provide multi-perceptual fr...

Understanding different perceptions of human being when using linguistic terms is a crucial issue in human-machine interaction. In this paper, we propose the concept of perceptual maps to model human opinions in a group decision-making context. The proposed approach considers a multi-granular structure using unbalanced hesitant linguistic term sets...

Global policy makers need to maintain a pulse on the state of play of global governance. Advances in analytical tools, such as global news dashboards, can provide current information on changes to global sentiment. In particular, identifying unexpected shifts in sentiment following a major news event may better inform stakeholders’ actions. This pa...

Advances in multi-attribute group decision making require the development of structures flexible enough to deal with unbalanced and multi-granular linguistic information. New distances between linguistic terms are needed to aggregate opinions and measure consensus among decision makers with different profiles. In this paper, firstly, based on the l...

People have come to refer to reviews for valuable information on products before making a purchase. Digesting relevant opinions regarding a product by reading all the reviews is challenging. An automated methodology which aggregates opinions across all the reviews for a single product to help differentiate any two products having the same overall r...

This paper focuses on analyzing the underlying sentiment of news articles, taken to be factual rather than comprised of opinions. The sentiment of each article towards a specific theme can be expressed in fuzzy linguistic terms and aggregated into a centralized sentiment which can be trended. This allows the interpretation of sentiments without con...

Becoming a smart city is one of the top priorities in the urban agenda of many European cities. Among the various strategies in the transition path, local governments seek to bring innovation to their cities by encouraging multinational enterprises to deploy their green energy services and products in their municipalities. Knowing how to attract th...

Curricula are an essential ingredient of academic activity in higher education institutions and so it is necessary to develop tools that help improve these curricula. The need to increase student employability has recently been highlighted as an objective for universities. This paper introduces a methodology to help assess curricula in the training...

Based on users’ interactions with social networks, a method to understand users’ life-styles is developed. Descriptions of their lifestyles are obtained from previously reported experiences on these sites. Contextual information and contributed reviews lend insight into which elements are important for different lifestyles. In this paper, an ordere...

Creating, designing and adjusting products are essential decision processes underlying creative industries, such as painting, perfume, food and beverage industries. These processes require the participation and continuous supervision of professionals with highly-developed expert sensory abilities. Training of these experts is very complex due to th...

Many destinations are implementing various water management alternatives to diminish the environmental impacts of tourism and increase sustainability. These efforts toward sustainability can be understood as part of corporate social responsibility (CSR) strategies implemented by tourism destinations. This paper is focused on the tourism destination...

This study attempts to gain a deeper understanding of the complex relationship between the brand color and brand personality perception by the customers. Combining data from a survey with accurate measurement of brand colors, a disaggregation analysis has been employed to identify how each component of brand color (hue, saturation, and brightness)...

Assigning papers to reviewers is a large, long and difficult task for conference chairs and scientific committees. The paper reviewer assignment problem is a multi-agent problem which requires understanding reviewer expertise and paper topics for the matching process. This paper proposes to elaborate on some features used to compute reviewer expert...

Present measures of the degree of agreement in group decision-making using hesitant fuzzy linguistic term sets allow consensus or agreement measurement when decision makers’ assessments involve hesitance. Yet they do not discriminate with different degrees of consensus among situations with discordant or polarized assessments. The visualization of...

In this paper we introduce a linguistic multi-criteria decision-aiding model to support college students with the internship job market application. It considers a fuzzy ordered weighted averaging (FOWA) operator in the matching to capture the inherent uncertainty and vague nature of personnel selection processes. The decision model is integrated i...

An additive value function is one of the prevailing preference models in Multiple Criteria Decision Aiding (MCDA). Its indirect elicitation through pairwise questions is often applied due to lowering the cognitive effort on the part of a Decision Maker (DM). A practical usefulness of this approach is influenced by both expressiveness of the assumed...

A new framework for preference disaggregation in multiple criteria decision aiding is introduced. The proposed approach aims to infer non-monotonic additive preference models from a set of indirect pairwise comparisons. The preference model is presented as a set of marginal value functions and the discriminatory power of the inferred preference mod...

Hesitant linguistic term sets have been introduced to capture the human way of reasoning using linguistic expressions involving different levels of precision. In this paper, a lattice structure is provided to the set of hesitant fuzzy linguistic term sets by means of the operations intersection and connected union. In addition, in a group decision...

Hesitant fuzzy linguistic term sets were introduced to grasp the uncertainty existing in human reasoning when expressing preferences. In this paper, an extension of the set of hesitant fuzzy linguistic term sets is presented to capture differences between non-compatible preferences. In addition, an order relation and two closed operation over this...

The use of computational intelligence for leveraging social creativity is a relatively new approach that allows organizations to find creative solutions to complex problems in which the interaction between stakeholders is crucial. The creative solutions that come from joint thinking?from the combined knowledge and abilities of people with diverse p...

Multi-criteria decision-making methods support decision makers in all stages of the decision-making process by providing useful data. However, criteria are not always certain as uncertainty is a feature of the real world. MCDM methods under uncertainty and fuzzy systems are accepted as suitable techniques in conflicting problems that cannot be repr...

This paper models the assessments of a group of experts when evaluating different magnitudes, features or objects by using linguistic descriptions. A new general representation of linguistic descriptions is provided by unifying ordinal and fuzzy perspectives. Fuzzy-qualitative labels are proposed as a generalization of the concept of qualitative la...

Given a finite totally ordered set of linguistic terms, the operations intersection and connected union provide a lattice structure to the set of hesitant fuzzy linguistic term sets. In this framework, hesitant fuzzy linguistic descriptions of a given set of alternatives are considered. A distance between hesitant fuzzy linguistic descriptions is i...

This work introduces new results on early-vocal development in infants and machines using artificial intelligent agents. It is addressed using the perspective of intrinsically-motivated learning algorithms for autonomous exploration. The agent autonomously selects goals to explore its own sensorimotor system in regions where a certain competence me...

Over the last few decades, fuzzy decision-making has attracted the attention of researchers and practitioners, offering as it does a way to represent and capture decision-making and consensual processes in a more flexible, human-like way. The importance of fuzzy reasoning in decision-making and consensus measurement lies in modelling forms of uncer...

What is the role that colour plays in perception of a brand by customers? How can we explore the cognitive role that colour plays in determining brand perception? To answer these questions we propose a preference disaggregation method based on multi-criteria decision aid. We identify the criteria aggregation model that underlies the global preferen...

A new formulation of the central ideas of Boden's well-established theory on combinational, exploratory and transformational creativity is presented. This new formulation, based on the idea of conceptual space, redefines some terms and includes several types of concept properties (appropriateness and relevance), whose relationship facilitates the c...

Similarity-based systems are considered to be of central interest for artificial intelligence and cognitive sciences research. Similarity-based systems describe analogies in human reasoning. The basic idea behind similarity-based systems is that reasoning concerned with either comparing different situations or analyzing new situations depends on th...

Performance measurement is a key issue when a company is designing new strategies to improve resource allocation. This paper offers a new methodology inspired by classic importance-performance analysis (IPA) that provides a global index of importance versus performance for firms. This index compares two rankings of the same set of features regardin...

A social multi-criteria evaluation framework for solving a real-case problem of selecting a wind farm location in the regions of Urgell and Conca de Barberá in Catalonia (northeast of Spain) is studied. This paper applies a qualitative multi-criteria decision analysis approach based on linguistic labels assessment able to address uncertainty and de...

This paper proposes a new model of consensus based on linguistic terms to be implemented in Delphi processes. The model of consensus involves qualitative reasoning techniques and is based on the concept of entropy. The proposed model has the ability to reach consensus automatically without the need for either a moderator or a final interaction amon...

This paper compares two multi-criteria decision making (MCDM) approaches based on linguistic label assessment. The first approach consists of a modified fuzzy TOPSIS methodology introduced by Kaya and Kahraman in 2011. The second approach, introduced by Agell et al. in 2012, is based on qualitative reasoning techniques for ranking multi-attribute a...

A new approach for Delphi processes including a measure of consensus based on linguistic terms is introduced in this paper. The measure of consensus involves qualitative reasoning techniques and is based on the concept of entropy. In the proposed approach, consensus is reached automatically without the need for neither a moderator nor a final inter...

El tsunami de datos que manejan las empresas puede ser una potente solución para mejorar la toma de decisiones. Ahora bien, esta cantidad y complejidad de datos se convierte en un problema indescifrable si no nos equipamos con técnicas de conversión, estudio e interpretación eficientes. La lógica difusa ha demostrado tener un papel clave en el anál...

In this paper we explore the possibility of capturing color trends and understanding the rationale behind the popularity of a color. To this end, we propose using a preference disaggregation approach from the field of Multi-Criteria Decision Analysis. The main objective is to identify the criteria aggregation model that underlies the global prefere...

A case study in a social multi-criteria evaluation framework for selecting a windfarm location in the regions of Urgell and La Conca de Barberà in Catalonia is presented. Two different MCDM approaches are introduced and compared through their application to the mentioned case. On the one hand, a Qualitative TOPSIS methodology able to address uncert...

In this paper, a new formulation of the central ideas of the well-established theory of Boden about creativity is presented. This new formulation redefines some terms and reviews the formal mechanisms of exploratory and transformational creativity. The presented approach is based on the conceptual space proposed by Boden and formalized by other aut...

In this paper a literature review on approaches for influencer detection in social networks is conducted. The paper contributes with a comparison between the three most popular influencer detection tools, with an analysis of their methods and algorithms and with a list of proposed extending capabilities.

Multi-Criteria Decision Aid (MCDA) methods include various collections of mathematical techniques related to decision support systems in non-deterministic environments to support such applications as facility management, disaster management and urban planning. This paper applies MCDA approaches based on qualitative reasoning techniques with linguis...

This paper presents a novel gait recognition method which uses the signals measured by a single inertial sensor located on the waist. This method considers human gait as a dynamical system and employs a few singular values obtained by means of Singular Spectrum Analysis applied to scalar measurements from the inertial sensor. Singular values can be...

We formally construct the extended set of qualitative labels L over a well-ordered set. The qualitative descriptions of a given set are defined as L-fuzzy sets. In the case where the well-ordered set is finite, a distance between L-fuzzy sets is introduced based on the properties of the lattice L. The concept of the information contained in a quali...

Creation and design of products based on human sensory perceptions, such as color, smell or taste, require the participation of professionals or experts with highly developed sensory abilities. When a group of experts is involved in such creative process as a team, consensus and group decision-making (GDM) techniques able to deal with qualitative d...

In this paper the design of a natural language generation (NLG) system is introduced to qualitatively describe the most important characteristics of each class, cluster or segment previously defined by means of a classification or clustering process. An adaptation of a generic architecture for data-to-text systems consisting of four stages is propo...

Gait Recognition is a biometric application that aims to identify a person by analyzing his/her gait. Common methods for gait recognition rely on supervised machine learning techniques and step detection methods. However, the latter has been showed to provide poor performances in ambulatory conditions [4]. In this paper, a Granular Computing approa...

This paper presents a new approach based upon qualitative reasoning techniques for representing and synthesising the information given by a group of evaluators. A mathematical formulation is developed that contributes to decision-making analysis in the context of multi-attribute and group decision-making. This method, is applied in choice and ranki...

Adjustment in creative processes is not purely a functional or a physical task, but arise from highly subjective preceptive and cognitive aspects which cannot be fully modeled by standard quantitative structures. In such tasks, the involvement of human experts becomes necessary, preventing the complete process automation. This paper introduces an i...

Gait Recognition is a biometric application that aims to identify a person by analyzing his/her gait. It is based on the fact that people often feel that they can identify a familiar person from afar simply by recognizing the way the person walks. In this work, a qualitative approach based on Granular computing paradigm is proposed. This paradigm i...

The aim of this chapter is to present a fuzzy segmentation model that combines statistical and Artificial Intelligence techniques to identify and quantify multifaceted consumers. One of the primary challenges faced by companies is getting to know their consumers. The latter are increasingly complex, versatile, ever-changing, and even contradictory;...

The aim of this chapter is to present a fuzzy segmentation model that combines statistical and Artificial Intelligence techniques to identify and quantify multifaceted consumers. One of the primary challenges faced by companies is getting to know their consumers. The latter are increasingly complex, versatile, ever-changing, and even contradictory;...

The aim of this chapter is to present a fuzzy segmentation model that combines statistical and Artificial Intelligence techniques to identify and quantify multifaceted consumers. One of the primary challenges faced by companies is getting to know their consumers. The latter are increasingly complex, versatile, ever-changing, and even contradictory;...

This chapter introduces a mathematical framework on the basis of the absolute order-of-magnitude qualitative model. This framework allows to develop a methodology to assess the consensus found among different evaluators who use ordinal scales in group decision-making and evaluation processes. The concept of entropy is introduced in this context and...

Ordinal scales are commonly used in rating and evaluation processes. These processes usually involve group decision making by means of an experts' committee. In this paper a mathematical framework based on the qualitative model of the absolute orders of magnitude is considered. The entropy of a qualitatively described system is defined in this fram...

This paper proposes a mathematical framework and methodology for group decision-making under multi-granular and multi-attribute linguistic assessments. It is based on distances between linguistic assessments and a degree of consensus. Distances in the space of qualitative assessments are defined from the geodesic distance in graph theory and the Mi...

In this work we compare the performance of some standard technical indicators with an interval technical indicator, the moving interval (MI), for time series forecasting. MI has the advantage of taking into account the variability of data in the range considered and not only the average, like standard indicators do. However, the use of intervals as...

The measurement of consensus and discrepancy among groups of evaluators is an important issue in group decision systems. These measurements will enable us to analyze the effort that should be made to obtain closer positions among subgroups. This paper presents a new approach, on the basis of the absolute order-of-magnitude qualitative model, to dec...

This paper presents a mathematical framework to assess the consensus found among different evaluators who use ordinal scales in group decision-making and evaluation processes. This framework is developed on the basis of the absolute order-of-magnitude qualitative model through the use of quantitative entropy. As such, we study the algebraic structu...

A growing body of literature established within the information technology field has focused on augmenting organizational knowledge and expertise. Due to increasing environmental complexity and changing technology the exogenous assumptions found within must be readdressed. Expert systems, group decision support systems, and collective intelligence...

This paper presents the foundation for a new methodology for a collaborative recommender system (RS). This methodology is based on the degree of consensus of a group of users stating their preferences via qualitative orders-of-magnitude. The structure of distributive lattice is considered in defining the distance between users and the RSs new users...

In this paper a new forecasting methodology to be used on time series prediction is introduced. The considered nonlinear method is based on support vector machines (SVM) using an interval kernel. An extended intersection kernel is introduced to discriminate between disjoint intervals in reference to the existing distance among them. The model prese...

This paper focuses on the mechanisms for knowledge generation and sharing in the co-creation process. Using a case study of an innovation intermediary we describe in detail the technical and non-technical mechanisms employed in the co-creation process. From this, the study suggests that co-creation is a pragmatic and iterative process for knowledge...

Kernel Machines, such as Support Vector Machines, have been frequently used, with considerable success, in situations in which the input variables were real values. Lately, these methods have also been extended to deal with discrete data such as string characters, microarray gene expressions, biosequences, etc. In this contribution we describe a ne...

This study provides insight from an evolutionary perspective of expertise that has shaped the field of decision support technologies. The investigation sets out to reveal the changing landscape of expertise in supporting decision-making using technology and sheds light on the new role that experts will play in organizational decision-making. The re...

In this work, a new technique to define cut-points in the discretization process of a continuous attribute is presented. This method is used as a prior step in a regression problem, considered as a learning problem in which the output variable can be either quantitative (continuous or discrete) or qualitative defined over an ordinal scale. The prop...

Organizations today face a changing environment, where external conditions change rapidly, organizational structures are more flat and dispersed, and where the traditional roles of experts have been "squeezed" or of decreased importance. These converging factors have importance for organizations' ability to remain competitive. These evolving trends...

This paper introduces a new approach to enhance learning in adjustment processes by using a support vector machine (SVM) algorithm as discriminant function jointly with an action generator module. The method trains a SVM with state-action patterns and uses trained SVM to select an appropriate action given a certain state in order to reach the targe...

This paper tries to determine, through the use of Support Vector Machines (SVM), the impact that technical indicators, a qualitative variable and the choice of free parameters selection have on a model's forecasting performance, power and accuracy applied to currency exchange rate prediction. This approach was applied to the weekly currency exchang...

A new iterative method based on Support Vector Machines to perform automated colour adjustment processing in the automotive in- dustry is proposed in this paper. The iterative methodology relies on a SVM trained with patterns provided by expert colourists and an ac- tions' generator module. The SVM algorithm enables selecting the most adequate acti...

This article introduces a new method for supervised discretization based on interval distances by using a novel concept of neighbourhood in the target's space. The method proposed takes into consideration the order of the class attribute, when this exists, so that it can be used with ordinal discrete classes as well as continuous classes, in the ca...

Abstract Correct default risk classification of an ,issuer is a critical factor. Practitioners and academics alike agree on this. Thus, under the supervision of financial experts, significant resources of investment advisory companies are used for this task. Researchers, both theoretical and empirical ones, are not the exception either. Nowadays, m...

The qualitative evaluation of chromatographic data in the framework of external quality assurance schemes is considered in this paper. The homogeneity in the evaluation of chromatographic data among human experts in samples with analytes close to the limit of detection of analytical methods was examined and also a Support Vector Machine (SVM) was d...

In this paper two kernels for interval data based on the intersection operation are introduced. On the one hand, it is demonstrated that the intersection length of two intervals is a positive definite (PD) kernel. On the other hand, a signed variant of this kernel, which also permits discriminating between disjoint intervals, is demonstrated to be...

This paper introduces the concept of entropy on orders of magnitude qualitative spaces and, consequently, the opportunity to measure the gain or loss of information when working with qualitative descriptions. The results obtained are significant in terms of situations which arise naturally in many real applications when dealing with different level...

Background, Aims and ScopeIn LCA the valuation step is very controversial since it involves value judgments. In order to strengthen the valuation step, this work establishes a new method, which includes normalization and weighting. Inspired by the proposal of Seppälä and Hämäläinen (2001), and based on the fuzzy sets theory (Zadeh 1965), this metho...

This work presents a short introduction to the main ideas be- hind the design of specific kernel functions when used by machine learn- ing algorithms, for example support vector machines, in the case that involved patterns are described by non-vectorial information. In partic- ular the interval data case will be analysed as an illustrating example:...

The use of unsupervised fuzzy learning methods produces a large number of alternative classifications. This paper presents and analyzes a series of criteria to select the most suitable of these classifications. Segmenting the clients' portfolio is important in terms of decision-making in marketing because it allows for the discovery of hidden profi...

The application of qualitative reasoning to learning algorithms can provide these models with the capability of automate common-sense and expert reasoning. Learning algorithms aim at automatically gathering the relevant information from a set of patterns and turn it into useful knowledge. That information usually comes from different sources and di...