Ramón Alberto Carrasco

Relaxing constraints in enhanced entity-relationship models using fuzzy quantifiers

While various articles about fuzzy entity relationship (ER) and enhanced entity relationship (EER) models have recently been published, not all examine how the constraints expressed in the model may be relaxed. In this paper, our aim is to relax the constraints which can be expressed in a conceptual model using the modeling tool, so that these constraints can be made more flexible. We will also study new constraints that are not considered in classic EER models. We use the fuzzy quantifiers which have been widely studied in the context of fuzzy sets and fuzzy query systems for databases. In addition, we shall examine the representation of these constraints in an EER model and their practical repercussions. The following constraints are studied: the fuzzy participation constraint, the fuzzy cardinality constraint, the fuzzy completeness constraint to represent classes and subclasses, the fuzzy cardinality constraint on overlapping specializations, fuzzy disjoint and fuzzy overlapping constraints on specializations, fuzzy attribute-defined specializations, fuzzy constraints in union types or categories and fuzzy constraints in shared subclasses. We shall also demonstrate how fuzzy (min, max) notation can substitute the fuzzy cardinality constraint but not the fuzzy participation constraint. All these fuzzy constraints have a new meaning, they offer greater expressiveness in conceptual design, and are included in the so-called fuzzy EER model.

A model for the integration of e-financial services questionnaires with SERVQUAL scales under fuzzy linguistic modeling

Although it is habitual to measure human perceptions with quite accurate instruments, perceptions are characterized by uncertainty and fuzziness. Furthermore, variations in individual perceptions and personality mean that the same words can indicate very different perceptions. In this context, the fuzzy linguistic approach seems to be an appropriate framework for modeling information. In this paper we explore the problem of integrating semantically heterogeneous data (natural language included) from various websites with opinions about e-financial services. We develop an extension of the fuzzy model based on semantic translation (FMST) under the perspective of the service quality (SERVQUAL) stream of research. The model permits us to obtain a more precise representation of the opinions using each type of customers. By integrating all customers into different subsets, a financial entity can easily analyze the SERVQUAL characteristics over time or other dimensions owing to the easy linguistic interpretability and high precision of the results of the model.

FEATURE SELECTION AND GRANULARITY LEARNING IN GENETIC FUZZY RULE-BASED CLASSIFICATION SYSTEMS FOR HIGHLY IMBALANCED DATA-SETS

This paper proposes a Genetic Algorithm for jointly performing a feature selection and granularity learning for Fuzzy Rule-Based Classification Systems in the scenario of highly imbalanced data-sets. We refer to imbalanced data-sets when the class distribution is not uniform, a situation that it is present in many real application areas. The aim of this work is to get more compact models by selecting the adequate variables and adapting the number of fuzzy labels for each problem, improving the interpretability of the model. The experimental analysis is carried out over a wide range of highly imbalanced data-sets and uses the statistical tests suggested in the specialized literature.

A Linguistic Multi-Criteria Decision Making Model Applied to the Integration of Education Questionnaires

We present a model made up of linguistic multi-criteria decision making processes to integrate the answers to heterogeneous questionnaires, based on a five-point Likert scale, into a unique form rooted in the widespread course experience questionnaire . The main advantage of having the resulting integrated questionnaire is that it can be incorporated into other course experience questionnaire surveys to make benchmarking among organizations. This model has been applied to integrate heterogeneous educational questionnaires at the University of Granada.

dmFSQL: a Language for Data Mining

At present, we have a FSQL server available for Oraclecopy databases which allow us to query a fuzzy or classical database with the FSQL (fuzzy SQL) language for any data type. The FSQL language is an extension of the SQL language, which permits us to write flexible conditions in our queries to a fuzzy or traditional database. In this paper, we proceed to extend FSQL into a new language called dmFSQL (data mining fuzzy structured query language) which can be used to solve real problems of clustering and classification. We consider that this model satisfies the requirements of data mining systems

Evaluation of the hotels e-services quality under the user's experience

While the SERVQUAL scale has met with greater success than other initiatives in the Internet context, the various adaptations and changes made to the measurement scales often make it difficult to compare results over time; a key aspect that companies must take into account when implementing their market-oriented strategies. Even when the time horizons are the same, it is often impossible to aggregate the results if different types of surveys and measurement scales are used; a practice which is, at the same time, customary. Moreover, the wide range of data collection methodologies and measurement scales used by different companies in the same market prevents comparing the results of surveys to evaluate service quality. In this paper, we present a linguistic multi-criteria decision-making model for aggregating these heterogeneous questionnaires with opinions about quality of the e-service offered by the hotels through several websites taking into account the experience on WWW of such users. The study found that all the scales have been slightly better evaluated for Travel 2.0 websites in general that for the studied hotel and established a ranking depending on the website from best to worst score on all SERVQUAL scales: hotel Tripadvisor webpage, hotel Facebook profile and official hotel blog.

A new model for linguistic summarization of heterogeneous data: an application to tourism web data sources

In this paper we present the problem of aggregating heterogeneous data from various websites with opinions about high end hotels into a database. We present the fuzzy model based on the semantic translation as a tool to obtain a linguistic summarization. The characteristics of this model (necessary to solve the problem) are not together on any of the existing linguistic models: the management of the input heterogeneous data (natural language included); the procurement of linguistic results with high precision and good interpretability; and the use of unbalanced linguistic term sets described by trapezoidal membership functions for defining the initial linguistic terms. We applied it to aggregate data from certain high end hotels websites and we show a case study using the high end hotels located in Granada (Spain) from such websites during a year. With this aggregated information, a data analyst can make several analyses with the benefit of easy linguistic interpretability and a high precision. The solution proposed here can be used to similar aggregation problems.

A hybrid model for decision-making in the Information and Communications Technology sector

The majority of businesses in the Information and Communications Technology (ICT) sector face decision-making problems on a daily basis. Most of these problems are based on contexts of uncertainty, where decisions are founded on qualitative information which may be imprecise or perception-based. In these cases, the information which is expressed by experts and users of evaluated services can be treated using processes of computing with words (CW). In this paper, we present a hybrid decision-making model especially designed for the ICT sector whereby the experts have the support of an intelligent system which provides information about the opinions of users related to those problems which are to be analysed. These opinions are obtained by using different mechanisms and techniques when users conduct business with the service provider. In addition, we employ a procedure for obtaining consensus between experts which enriches and strengthens the decision-making process.

Fuzzy integration of web data sources for data warehousing

In this paper we show our work related to an approach for monitoring web sources on the World Wide Web using its temporal properties in order to integrate them in a temporal Data Warehouse. We use these temporal properties obtained for integrating data more efficiently from different data sources according to the requirements of the Data Warehouse administrator. For this integration process we proposed a parallel fuzzy temporal semantic algorithm based on a flexible query language called FSQL in order to obtain more precise data in the Data Warehouse. In addition, we show an application applied to tourism area where data integrated into Data Warehouse can be used to schedule personalized travel as a value-added service for electronic commerce.

Fuzzy constraints using the enhanced entity-relationship model

Our aim is to relax the constraints which can be expressed in a conceptual model using the enhanced entity-relationship (EER) modelling tool, so that these constraints can be made more flexible. To do so, we use the fuzzy quantifiers which have been widely studied in the context of fuzzy sets and fuzzy consultation systems for databases. We also examine the representation of these constraints in an EER model and their practical repercussions. The constraints proposed are as follows: a fuzzy participation constraint, a fuzzy cardinality constraint, a fuzzy completeness constraint in the representation of classes and sub-classes (and categories or union types) and a fuzzy cardinality constraint in overlapping specialization. We also demonstrate how a fuzzy (min, max) notation can substitute for the fuzzy cardinality constraints. All these fuzzy constraints have a novel meaning and offer greater expressiveness in conceptual design.