1,088 research outputs found
A New Rational Algorithm for View Updating in Relational Databases
The dynamics of belief and knowledge is one of the major components of any
autonomous system that should be able to incorporate new pieces of information.
In order to apply the rationality result of belief dynamics theory to various
practical problems, it should be generalized in two respects: first it should
allow a certain part of belief to be declared as immutable; and second, the
belief state need not be deductively closed. Such a generalization of belief
dynamics, referred to as base dynamics, is presented in this paper, along with
the concept of a generalized revision algorithm for knowledge bases (Horn or
Horn logic with stratified negation). We show that knowledge base dynamics has
an interesting connection with kernel change via hitting set and abduction. In
this paper, we show how techniques from disjunctive logic programming can be
used for efficient (deductive) database updates. The key idea is to transform
the given database together with the update request into a disjunctive
(datalog) logic program and apply disjunctive techniques (such as minimal model
reasoning) to solve the original update problem. The approach extends and
integrates standard techniques for efficient query answering and integrity
checking. The generation of a hitting set is carried out through a hyper
tableaux calculus and magic set that is focused on the goal of minimality.Comment: arXiv admin note: substantial text overlap with arXiv:1301.515
Disjunctively incomplete information in relational databases: modeling and related issues
In this dissertation, the issues related to the information incompleteness in relational databases are explored. In general, this dissertation can be divided into two parts. The first part extends the relational natural join operator and the update operations of insertion and deletion to I-tables, an extended relational model representing inclusively indefinite and maybe information, in a semantically correct manner. Rudimentary or naive algorithms for computing natural joins on I-tables require an exponential number of pair-up operations and block accesses proportional to the size of I-tables due to the combinatorial nature of natural joins on I-tables. Thus, the problem becomes intractable for large I-tables. An algorithm for computing natural joins under the extended model which reduces the number of pair-up operations to a linear order of complexity in general and in the worst case to a polynomial order of complexity with respect to the size of I-tables is proposed in this dissertation. In addition, this algorithm also reduces the number of block accesses to a linear order of complexity with respect to the size of I-tables;The second part is related to the modeling aspect of incomplete databases. An extended relational model, called E-table, is proposed. E-table is capable of representing exclusively disjunctive information. That is, disjunctions of the form P[subscript]1\mid P[subscript]2\mid·s\mid P[subscript]n, where Ç denotes a generalized logical exclusive or indicating that exactly one of the P[subscript]i\u27s can be true. The information content of an E-table is precisely defined and relational operators of selection, projection, difference, union, intersection, and cartisian product are extended to E-tables in a semantically correct manner. Conditions under which redundancies could arise due to the presence of exclusively disjunctive information are characterized and the procedure for resolving redundancies is presented;Finally, this dissertation is concluded with discussions on the directions for further research in the area of incomplete information modeling. In particular, a sketch of a relational model, IE-table (Inclusive and Exclusive table), for representing both inclusively and exclusively disjunctive information is provided
Treatment of imprecision in data repositories with the aid of KNOLAP
Traditional data repositories introduced for the needs of business
processing, typically focus on the storage and querying of crisp
domains of data. As a result, current commercial data repositories
have no facilities for either storing or querying imprecise/
approximate data.
No significant attempt has been made for a generic and applicationindependent
representation of value imprecision mainly as a
property of axes of analysis and also as part of dynamic
environment, where potential users may wish to define their âownâ
axes of analysis for querying either precise or imprecise facts. In
such cases, measured values and facts are characterised by
descriptive values drawn from a number of dimensions, whereas
values of a dimension are organised as hierarchical levels.
A solution named H-IFS is presented that allows the representation
of flexible hierarchies as part of the dimension structures. An
extended multidimensional model named IF-Cube is put forward,
which allows the representation of imprecision in facts and
dimensions and answering of queries based on imprecise
hierarchical preferences. Based on the H-IFS and IF-Cube
concepts, a post relational OLAP environment is delivered, the
implementation of which is DBMS independent and its performance
solely dependent on the underlying DBMS engine
On various forms of bipolarity in flexible querying
International audienceThe paper discusses the modeling of âif possible" in requirements of the form âA and if possible B". We distinguish between two types of understanding: either i) A and B are requirements of the same nature and are viewed as constraints with different levels of priority, or ii) they are of different nature (only A induces constraint(s) and B is only used for breaking ties among items that are equally satisfying A). We indicate that the two views are related to different types of bipolarity, and discuss them in relation with possibilistic logic. The disjunctive dual of the first view (âA or at least B") is then presented in this logical setting. We also briefly mention the idea of an extension of the second view where B may refer both to bonus conditions or malus conditions that may increase or decrease respectively the interest in an item satisfying A
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
Class Association Rules Mining based Rough Set Method
This paper investigates the mining of class association rules with rough set
approach. In data mining, an association occurs between two set of elements
when one element set happen together with another. A class association rule set
(CARs) is a subset of association rules with classes specified as their
consequences. We present an efficient algorithm for mining the finest class
rule set inspired form Apriori algorithm, where the support and confidence are
computed based on the elementary set of lower approximation included in the
property of rough set theory. Our proposed approach has been shown very
effective, where the rough set approach for class association discovery is much
simpler than the classic association method.Comment: 10 pages, 2 figure
Data modeling dealing with uncertainty in fuzzy logic
This paper shows models of data description that incorporate uncertainty like models of data extension EER, IFO among others. These database modeling tools are compared with the pattern FuzzyEER proposed by us, which is an extension of the EER model in order to manage uncertainty with fuzzy logic in fuzzy databases. Finally, a table shows the components of EER tool with the representation of all the revised models.The past and the future of information systems: 1976-2006 and beyondRed de Universidades con Carreras en InformĂĄtica (RedUNCI
Consultas difusas en asistencia al diagnóstico médico
This paper proposes the utilization of a fuzzy database engine for supporting medical diagnoses. Expert know how is stored in a relational database and then it is modeled diagnoses rules with fuzzy queries that pulls out the most accurate information related to the sickness and therefore supporting doctors with the medical diagnostic. A solution prototype has been developed with information related to respiratory disease characterization and it is built with fuzzy queries using SQLf. This case study can be used to define a roadmap for future developments in medical diagnosis supported on fuzzy databases. As always, the diagnosis can only be given by a specialist, these systems only provide help in their work task.Este artĂculo propone el uso de un motor de base de datos difuso para ayudar en el diagnĂłstico mĂ©dico. El conocimiento experto se almacena en una base de datos relacional y luego se modela mediante reglas de diagnĂłstico con consultas difusa que extraen la informaciĂłn mĂĄs precisa relacionada con la enfermedad y, por lo tanto, apoyan a los mĂ©dicos con el diagnĂłstico mĂ©dico. Hemos construido un prototipo de sistema con una base de datos que almacena la caracterizaciĂłn de enfermedades respiratorias. Esta aplicaciĂłn se ha creado utilizando un sistema de gestiĂłn de bases de datos que admite el lenguaje de consulta difusa SQLf. Este trabajo encamina desarrollos futuros en el diagnĂłstico mĂ©dico soportado sobre bases de datos difusas. Como siempre, el diagnĂłstico solo puede ser dado por un especialista, estos sistemas solo brindan ayuda en su labor mĂ©dica
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