Constraint-wish and satisfied-dissatisfied: an overview of two approaches for dealing with bipolar querying

In recent years, there has been an increasing interest in dealing with user preferences in flexible database querying, expressing both positive and negative information in a heterogeneous way. This is what is usually referred to as bipolar database querying. Different frameworks have been introduced to deal with such bipolarity. In this chapter, an overview of two approaches is given. The first approach is based on mandatory and desired requirements. Hereby the complement of a mandatory requirement can be considered as a specification of what is not desired at all. So, mandatory requirements indirectly contribute to negative information (expressing what the user does not want to retrieve), whereas desired requirements can be seen as positive information (expressing what the user prefers to retrieve). The second approach is directly based on positive requirements (expressing what the user wants to retrieve), and negative requirements (expressing what the user does not want to retrieve). Both approaches use pairs of satisfaction degrees as the underlying framework but have different semantics, and thus also different operators for criteria evaluation, ranking, aggregation, etc

Bipolarity in ear biometrics

Identifying people using their biometric data is a problem that is getting increasingly more attention. This paper investigates a method that allows the matching of people in the context of victim identification by using their ear biometric data. A high quality picture (taken professionally) is matched against a set of low quality pictures (family albums). In this paper soft computing methods are used to model different kinds of uncertainty that arise when manually annotating the pictures. More specifically, we study the use of bipolar satisfaction degrees to explicitly handle the bipolar information about the available ear biometrics

Problems and opportunities of applying data-& audio-mining techniques to ethnic music

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Bipolar fuzzy querying of temporal databases

Temporal databases handle temporal aspects of the objects they describe with an eye to maintaining consistency regarding these temporal aspects. Several techniques have allowed these temporal aspects, along with the regular aspects of the objects, to be defined and queried in an imprecise way. In this paper, a new technique is proposed, which allows using both positive and negative -possibly imprecise- information in querying relational temporal databases. The technique is discussed and the issues which arise are dealt with in a consistent way

The bipolar semantics of querying null values in regular and fuzzy databases: dealing with inapplicability

Dealing with missing information in databases, either because the information is unknown or inapplicable, is a widely addressed topic in research. Most of the time, null values are used to model this missing information. This paper deals with querying such null values, and more specifically null values representing inapplicable information, and tries to come up with semantically richer, but still correct, query answers in the presence of mill values. The presented approach is based on the observation that, when used in the context of a query, an inapplicable value can be treated semantically equivalent to some other regular domain value, resulting in a query criteria satisfaction being either 'true', 'false' or 'unknown'. So, the data itself can be inapplicable, but the criteria (and query) satisfaction is not inapplicable