Ignacio J. Blanco

Ignacio J. Blanco
University of Granada | UGR · Department of Computer Science and Artificial Intelligence

PhD

About

63
Publications
24,647
Reads
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724
Citations
Citations since 2017
6 Research Items
244 Citations
201720182019202020212022202301020304050
201720182019202020212022202301020304050
201720182019202020212022202301020304050
201720182019202020212022202301020304050
Additional affiliations
February 2004 - May 2020
University of Granada
Position
  • Professor (Associate)
January 2002 - February 2004
Universidad de Almería
Position
  • Professor (Assistant)
January 1998 - January 2002
Universidad de Granada
Position
  • Research Grant Holder
Education
January 1998 - July 2001
University of Granada
Field of study
  • Computer Science
October 1992 - December 1997
University of Granada
Field of study
  • Computer Science

Publications

Publications (63)
Conference Paper
Full-text available
En problemas del mundo real, las bases de datos no son estáticas, y la información se actualiza continuamente. Un ejemplo son los datos procedentes de entornos inteligentes. Precisamente, el análisis de dicha información mediante técnicas tradicionales de minería de datos puede verse dificultado por esta continua variación. En este trabajo se resum...
Article
Big Data are a paradigm through which valuable information is achieved through the analysis of a large amount of data. The sources of these data can be varied, from data streams that will be processed in real time, to the exploitation of transactional data stored in databases. For this last use, due to their scalability, the NoSQL databases, like m...
Article
Full-text available
Fuzzy association rules (FARs) are a recognized model to study existing relations among data, commonly stored in data repositories. In real-world applications, transactions are continuously processed with upcoming new data, rendering the discovered rules information inexact or obsolete in a short time. Incremental mining methods arise to avoid re-r...
Article
This work presents an overview of the text mining area, considering the most common techniques, and including proposals based on the application of fuzzy sets. Besides, some of the most frequent text mining applications are mentioned. We discuss the existing approaches, which we call text data mining, in relation to the recently proposed paradigm o...
Chapter
Full-text available
Predicting students’ academic performance is one of the oldest and most popular applications of educational data mining. It helps to estimate the unknown evaluation of a student’s performance. However, a huge amount of data with different formats and from multiple sources may contain a large number of features supposed as not-relevant that could in...
Conference Paper
A wide spectrum of methods for knowledge extraction have been proposed up to date. These expensive algorithms become inexact when new transactions are made into business data, an usual problem in real-world applications. The incremental maintenance methods arise to avoid reruns of those algorithms from scratch by reusing information that is systema...
Article
Full-text available
Association Rules (ARs) and Approximate Dependencies (ADs) are significant fields in data mining and the focus of many research efforts. This knowledge, extracted by traditional mining algorithms becomes inexact when new data operations are executed, a common problem in real-world applications. Incremental mining methods arise to avoid re-runs of thos...
Conference Paper
Full-text available
El aprendizaje permanente (LifeLong Learning) es cada vez más im-portante y necesario en una sociedad que evoluciona sobre modelos productivos basados en nuevas formas de gestión de la información. Internet es tanto un medio de transmisión como una fuente de información cada vez más importante en todo este proceso. En este artículo abordaremos las...
Chapter
Full-text available
Resumen La introducción de las Tecnologías de la Información y de la Comunicación (TIC) en las universidades está provocando profundos cambios en el mundo académico por su indudable potencial para el desarrollo de la docencia, la gestión y la investigación. Sin embargo, al analizar este proceso se puede comprobar que no es un simple cambio de herra...
Article
Full-text available
Several applications to represent classical or fuzzy data in databases have been developed in the last two decades. However, these representations present some limitations specially related with the system portability and complexity. Ontologies provides a mechanism to represent data in an implementation-independent and web-accessible way. To get ad...
Article
Full-text available
Two main data models are currently used for representing knowledge and information in computer systems. Database models, especially relational databases, have been the leader in last few decades, enabling information to be efficiently stored and queried. On the other hand, ontologies have appeared as an alternative to databases in applications that...
Article
Fuzzy data management in databases is a complex process because of flexible data nature and heterogeneous database systems. A solution to this problem has been solved using an ontology which isolates the fuzzy database representation of their management platform making fuzzy schemas Relational Database Management System (RDBMS)-independent and Web-...
Conference Paper
Time in databases has been studied for a long time. Valid time databases capture when the objects are true in the reality. The proposed model allows both representing and querying time in a fuzzy way. The representation and the underlying domain are defined as well as some fuzzy temporal operators. The implementation of the model is developed withi...
Conference Paper
Fuzzy databases manage imprecision in its schema and offer tools for flexible querying. A true standard does not exist. Relational databases are usually the base for the implementation of fuzzy databases. In this paper we propose a general model to represent and querying fuzzy types in any relational database. The model is implemented within the Hi...
Conference Paper
A fuzzy database has two main features: flexible querying and representation of imprecision or vagueness. The first feature allows querying in linguistic terms.(i.e. selections in terms of age labels like 'young' or 'middle-aged' customers). The representation of vagueness is done by means of possibility distributions and fuzzy constants like 'UNKN...
Conference Paper
Different communication mechanisms between ontologies and database (DB) systems have appeared in the last few years. However, several problems can arise during this communication, depending on the nature of the data represented and their representation structure, and these problems are often enhanced when a Fuzzy Database (FDB) is involved. An arch...
Chapter
The Semantic Web has resulted in a wide range of information (e.g., HML, XML, DOC, PDF documents, ontologies, interfaces, forms, etc.) being made available in semantic queries, and the only requirement is that these are described semantically. Generic Web interfaces for querying databases (such as ISQLPlus ©) are also part of the Semantic Web, but...
Conference Paper
Full-text available
In this paper we introduced an alternative view of text mining and we review several alternative views proposed by different authors. We propose a classification of text mining techniques into two main groups: techniques based on inductive inference, that we call text data mining (TDM, comprising most of the existing proposals in the literature), a...
Conference Paper
Full-text available
In this paper we review several alternative views of text mining (TM) as proposed by different authors, and we introduce our own view. We propose a classification of TM tech-niques on two main groups: techniques based on inductive inference, that we call text data mining (TDM, comprising most of the ex-isting proposals in the literature), and tech-...
Article
Full-text available
In this paper we deal with the problem of mining for approximate dependencies (AD) in relational databases. We introduce a definition of AD based on the concept of association rule, by means of suitable definitions of the concepts of item and transaction. This definition allow us to measure both the accuracy and support of an AD. We provide an inte...
Article
This paper presents GDB, a system to build, debug and test rules in a Fuzzy Relational Deductive Database System (FRDDS) in a visual way avoiding the associated syntax which could be quite complex for a non-expert user. The rules will be used to compute a Measure of Quality (MoQ) of the scientific data generated by the GIADA instrument (ROSETTA spa...
Article
In this paper, an ontology system is proposed to represent the knowledge structure enabling fuzzy information to be stored in fuzzy databases. This proposal allows users or applications to simplify the metadata definition process that is necessary for representing and managing imprecise and classic information in these databases. This ontology then...
Article
The Semantic Web has resulted in a wide range of information (e.g., HML, XML, DOC, PDF documents, ontologies, interfaces, forms, etc.) being made available in semantic queries, and the only requirement is that these are described semantically. Generic Web interfaces for querying databases (such as ISQLPlus ©) are also part of the Semantic Web, but...
Chapter
The Semantic Web has resulted in a wide range of information (e.g., HML, XML, DOC, PDF documents, ontologies, interfaces, forms, etc.) being made available in semantic queries, and the only requirement is that these are described semantically. Generic Web interfaces for querying databases (such as ISQLPlus©) are also part of the Semantic Web, but t...
Conference Paper
Abstract This paper proposes an ontology which enables fuzzy data to be deflned in order to conceptualize them and to represent another type of informa- tion. The Fuzzy Knowledge Representation On- tology described is based on the fuzzy data theo- retical model, and a method for classifying both classical and fuzzy data is proposed. This on- tology...
Article
In the analysis of data stored in databases, a very interesting issue is the detection of possible existing relations between attribute values and, at an upper level, relations between attributes themselves. In case uncertainty is present in data, or it is introduced in a pre-processing step, specific data mining and knowledge discovery techniques...
Article
Full-text available
In this paper, an architecture and an implementation of a multipurpose relational database server are proposed. This architecture enables classical queries to be executed, deductions to be made, and data mining operations to be performed on fuzzy or classical data. The proposal of this integration is to combine several ways of querying different ty...
Article
Full-text available
In this paper, we define the concept of generalized rule for making classical deduction with imprecise data, stored both data and rules in a fuzzy relational database represented in the GEFRED model. We propose a way of measuring the imprecision related to the calculation of a fact based on the matching degree of the facts in the database and the f...
Conference Paper
This paper presents a new way of giving the summary of a numerical attribute involved in a fuzzy query. It is based on the idea of offering a linguistic interpretation, therefore we propose to use a flat fuzzy number as summary. To obtain it, we optimize any index which measures the relation between the fuzzy bag (which is the answer to the fuzzy q...
Conference Paper
Full-text available
In this paper, some considerations on ex-tension of the Datalog language are pro-posed in order to apply this language on a GEFRED fuzzy relational database. For this integration, we use some extended com-parators from the GEFRED model and an existing generalization of the concept of rule to work with flexible values.
Article
Full-text available
It has been pointed out that the usual framework to assess association rules, based on support and confidence as measures of importance and accuracy, has several drawbacks. In particular, the presence of items with very high support can lead to obtain many misleading rules, even in the order of 95% rules in some of our experiments. In this paper we...
Article
Fuzzy Types are a desirable feature that an Object Oriented Database System (OODB) must have in order to deal with vague structures. This kind of types are defined by means of different levels of precision or amplitude where properties are ordered according to their relationship with the concept represented by the type. The implementation of this n...
Conference Paper
Full-text available
The evaluation of quantified sentences of the form "Q of D are A" is recognized as a suitable tool for quantifier guided aggregation of fuzzy criteria with associated importances. In this paper we discuss the properties any good evaluation method should verify. We study a new method to evaluate quantified sentences. Our new method is shown to be an...
Conference Paper
The usual support/confidence framework to assess association rules has several drawbacks that lead to obtain many misleading rules, even in the order of 95% of the discovered rules in some of our experiments. In this paper we introduce a different framework, based on Shortliffe and Buchanan’s certainty factors and the new concept of very strong rul...
Conference Paper
Object-oriented databases have proved to be a good alternative to the relational ones of Codd when dealing with applications characterized by their complexity and dynamism. A big part of the effort of researchers in the field of object-oriented databases (OODB) has been focused on the study of the addition of vagueness to this database model. There...
Conference Paper
In this paper, we extend an existing relational language such as SQL with capabilities for representing and handling imprecise information. We add new sentences to manage new types based on a domain concept extension. New values for these types are added, including three ones for a more specialized management of NULL values.
Chapter
This chapter shows how to integrate the representation of deductive rules and fuzzy information stored in a relational DBMS to build a module that can obtain new data from data stored in tables. The deductions can be applied to classical (or precise) data, imprecise data or both of them, so it is necessary to provide a mechanism to find the tuples...

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