Erratum to: Database preference queries - a possibilistic logic approach with symbolic priorities.

International audienceThis note corrects a claim made in the above-mentioned paper about the exact representation of a conditional preference network by means of a possibilistic logic base with partially ordered symbolic weights. We provide a counter-example that shows that the possibilistic logic representation is indeed not always exact. This is the basis of a short discussion on the difficulty of obtaining an exact representation

Weakening of fuzzy relational queries: an absolute proximity relation-based approach

In this paper we address the problem of query failure in the context of flexible querying. We propose a fuzzy set–based approach for relaxing queries involving gradual predicates. This approach relies on the notion of proximity relation which is defined in an absolute way. We show how such proximity relation allows for transforming a given predicate into an enlarged one. The resulting predicate is semantically not far from the original one and it is obtained by a simple fuzzy arithmetic operation. The main features of the weakening mechanism are investigated and a comparative study with some methods proposed for the purpose of fuzzy query weakening is presented as well. Last, an example is provided to illustrate our proposal in the case of conjunctive queries.Peer Reviewe

Conditional Preference Nets and Possibilistic Logic

International audienceCP-nets (Conditional preference networks) are a well-known compact graphical representation of preferences in Artificial Intelligence, that can be viewed as a qualitative counterpart to Bayesian nets. In case of binary attributes it captures specific partial orderings over Boolean interpretations where strict preference statements are defined between interpretations which differ by a single flip of an attribute value. It respects preferential independence encoded by the ceteris paribus property. The popularity of this approach has motivated some comparison with other preference representation setting such as possibilistic logic. In this paper, we focus our discussion on the possibilistic representation of CP-nets, and the question whether it is possible to capture the CP-net partial order over interpretations by means of a possibilistic knowledge base and a suitable semantics. We show that several results in the literature on the alleged faithful representation of CP-nets by possibilistic bases are questionable. To this aim we discuss some canonical examples of CP-net topologies where the considered possibilistic approach fails to exactly capture the partial order induced by CP-nets, thus shedding light on the difficulties encountered when trying to reconcile the two frameworks

Weakening of fuzzy relational queries: an absolute proximity relation-based approach

In this paper we address the problem of query failure in the context of flexible querying. We propose a fuzzy set–based approach for relaxing queries involving gradual predicates. This approach relies on the notion of proximity relation which is defined in an absolute way. We show how such proximity relation allows for transforming a given predicate into an enlarged one. The resulting predicate is semantically not far from the original one and it is obtained by a simple fuzzy arithmetic operation. The main features of the weakening mechanism are investigated and a comparative study with some methods proposed for the purpose of fuzzy query weakening is presented as well. Last, an example is provided to illustrate our proposal in the case of conjunctive queries.Peer Reviewe

On the Versatility of Fuzzy Sets for Modeling Flexible Queries

The idea of extending the usual Boolean queries with preferences has become a hot topic in the database community. One of the advantages of this approach is to deliver discriminated answers rather than flat sets of elements. Fuzzy sets are a natural means to represent preferences, and many works have been undertaken to define queries where fuzzy predicates can be introduced inside user queries. The objective of this chapter is to illustrate the expressiveness of fuzzy sets with the division operator in the context of regular databases. Like other operators, the regular division is not flexible at all and small variations in the data may lead to totally different results. To counter this behavior, a variety of extended division operators founded on fuzzy sets are suggested. All of them obey a double requirement: to have a clear meaning from a user point of view and to deliver a resulting relation which is a quotient.</jats:p