IRISA ENSSAT

Lannion, France

IRISA ENSSAT

Lannion, France

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Pivert O.,University of Rennes 1 | Smits G.,Irisa Enssat | Jaudoin H.,University of Rennes 1
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2013

This paper deals with the issue of extending the scope of a user query in order to retrieve objects which are similar to its "strict answers". The approach proposed exploits associations between database items, corresponding, e.g., to the presence of foreign keys in the database schema. Fuzzy concepts such as typicality, similarity and linguistic quantifiers are at the heart of the approach and make it possible to obtain a ranked list of similar answers. © 2013 Springer-Verlag Berlin Heidelberg.


Bosc P.,IRISA ENSSAT | Pivert O.,IRISA ENSSAT | Prade H.,French National Center for Scientific Research
Proceedings of the 2010 International Conference of Soft Computing and Pattern Recognition, SoCPaR 2010 | Year: 2010

In this paper, we consider relational databases containing uncertain attribute values, in the situation where some knowledge is available about the more or less certain value (or disjunction of values) that a given attribute in a tuple can take. We propose a possibility-theory-based model suited to this context and extend the operators of relational algebra in order to handle such relations in a "compact" thus efficient way. It is shown that the proposed model is a strong representation system for the whole relational algebra. An important result is that the data complexity associated with the extended operators in this context is the same as in the classical database case, which makes the approach highly scalable. © 2010 IEEE.


Akaichi J.,BESTMOD Laboratory | Lietard L.,IRISA ENSSAT | Rocacher D.,IRISA ENSSAT | Slama O.,IRISA ENSSAT
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2015

This article considers the bipolar approach to define database queries expressing users’ preferences (flexible queries). An algebraic framework for the definition of flexible queries of relational databases using fuzzy bipolar conditions of type and-if-possible and or-else has been considered. This paper defines some qualitative calibrations of such queries to specify a minimal quality of answers and to reduce their number. Different operators (extended α-cuts) are defined and studied in this article. They can apply on the set of answers to express a qualitative calibrations of bipolar fuzzy queries. Some properties of these extended α-cuts are pointed out and some of their applications for query evaluation are shown. © Springer International Publishing Switzerland 2015.


Abbaci K.,IRISA ENSSAT | Hadjali A.,LIAS ENSMA | Lietard L.,IRISA ENSSAT | Rocacher D.,IRISA ENSSAT
Proceedings of the 2013 Joint IFSA World Congress and NAFIPS Annual Meeting, IFSA/NAFIPS 2013 | Year: 2013

Skyline queries are a popular and powerful paradigm for extracting interesting objects from a d-dimensional dataset. They rely on Pareto dominance principle to identify the skyline objects, i.e., the set of incomparable objects which are not dominated by any other object from the dataset. Two main problems may be faced when using skyline queries: (i) a small number of returned objects which could be insufficient for the users' needs; and (ii) a huge number of skyline objects which is less informative for the users. In this paper, we tackle the last problem and propose an approach to deal with it. The idea consists in refining the skyline in order to discriminate its elements and select the best ones. A new definition of dominance relationship based on the fuzzy quantifier 'almost all' is then introduced. © 2013 IEEE.


Smits G.,IRISA IUT | Pivert O.,IRISA ENSSAT | Hadjali A.,IRISA ENSSAT
Studies in Computational Intelligence | Year: 2014

Cooperative approaches to relational database querying help users retrieve the tuples that are the most relevant with respect to their information needs. In this chapter we propose a unified framework that relies on a fuzzy cardinality-based summary of the database. We show how this summary can be efficiently used to explain failing queries or to revise queries returning a plethoric answer set. © 2014 Springer International Publishing Switzerland.


Abbaci K.,IRISA ENSSAT | Hadjali A.,IRISA ENSSAT | Lietard L.,IRISA IUT | Rocacher D.,IRISA ENSSAT
Proceedings - International Conference on Data Engineering | Year: 2011

One of the fundamental problems in graph databases is similarity search for graphs of interest. Existing approaches dealing with this problem rely on a single similarity measure between graph structures. In this paper, we suggest an alternative approach allowing for searching similar graphs to a graph query where similarity between graphs is rather modeled by a vector of scalars than a unique scalar. To this end, we introduce the notion of similarity skyline of a graph query defined by the subset of graphs of the target database that are the most similar to the query in a Pareto sense. The idea is to achieve a d-dimensional comparison between graphs in terms of d local distance (or similarity) measures and to retrieve those graphs that are maximally similar in the sense of the Pareto dominance relation. A diversity-based method for refining the retrieval result is proposed as well. © 2011 IEEE.


Pivert O.,IRISA ENSSAT | Hadjali A.,IRISA ENSSAT | Smits G.,IRISA IUT
2010 IEEE International Conference on Intelligent Systems, IS 2010 - Proceedings | Year: 2010

In this paper, we consider the situation where a fuzzy query is submitted to distributed data sources. In order to save bandwith and processing cost, we propose a technique whose aim is to forward the query to the most relevant sources only. It is assumed that a fuzzy summary of every data source is available, and the approach we propose consists in estimating the relevance of a source wrt to a user query, based on its associated summary. The general case where the user does not necessarily employ the vocabulary (i.e., the labels from the fuzzy partitions) that was used for summarizing the source is considered. © 2010 IEEE.


Pivert O.,Irisa Enssat | Hadjali A.,Irisa Enssat | Smits G.,Irisa Enssat
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2011

This paper deals with database preference queries involving fuzzy conditions which do not explicitly refer to an attribute from the database, but whose meaning is rather inferred from a set of rules. The approach we propose, which is based on some concepts from the fuzzy control domain (aggregation and defuzzification, in particular), significantly increases the expressivity of fuzzy query languages inasmuch as it allows for new types of predicates. An implementation strategy involving a coupling between a DBMS and a fuzzy reasoner is outlined. © 2011 Springer-Verlag Berlin Heidelberg.


Lietard L.,IRISA ENSSAT
Information Sciences | Year: 2012

This article concerns the definition of linguistic summaries of data in the relational model of databases. Among the different approaches, the propositions calling on linguistic quantifiers are very appealing since they offer flexibility and a linguistic formulation which can be easily understood by a user. More precisely, these linguistic summaries are made of a quantified statement associated with a degree of validity (computed from the database). Such a summary shows that a quantity of information (quantity described by the linguistic quantifier) satisfies a constraint (defined by a fuzzy predicate). This article shows that the already proposed approaches do not sufficiently stress the relationship between these two aspects. As a consequence, we propose another kind of linguistic summaries made of a linguistic statement associated with a degree of validity having a clear meaning in terms of quantity and quality. It becomes possible to compare two linguistic summaries and to understand the difference in their degrees of validity. These summaries are called functional linguistic summaries because their interpretation relies on a particular set-oriented function. They present the advantages of using fuzzy terms to reflect that the user does not exactly know what can be expected from the database. However, the degree of validity provides a precise description of the stored information. In other words, starting from a rough idea of what can be expected as a summary, the obtained degree of truth provides a precise description of the information stored in the database. The relationship of the proposed linguistic summaries with the quantified statements are studied in this paper. It turns out that these linguistic summaries can be viewed as particular quantified statements having particular properties. © 2011 Elsevier Inc. All rights reserved.


Bosc P.,IRISA ENSSAT | Pivert O.,IRISA ENSSAT
Studies in Fuzziness and Soft Computing | Year: 2013

Many authors have made proposals to model and handle databases involving uncertain data. In particular, the last two decades have witnessed a blossoming of researches on this topic (cf. e.g., [3,4,19] for some recent ones). Even though most of the literature about uncertain databases uses probability theory as the underlying uncertainty model, some approaches rather rest on possibility theory [26]. The initial idea consisting in applying possibility theory to this issue goes back to the early 80's [24]. More recent advances on this topic can be found in [10]. © 2013 Springer-Verlag Berlin Heidelberg.

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