30,144 research outputs found
Explicit probabilistic models for databases and networks
Recent work in data mining and related areas has highlighted the importance
of the statistical assessment of data mining results. Crucial to this endeavour
is the choice of a non-trivial null model for the data, to which the found
patterns can be contrasted. The most influential null models proposed so far
are defined in terms of invariants of the null distribution. Such null models
can be used by computation intensive randomization approaches in estimating the
statistical significance of data mining results.
Here, we introduce a methodology to construct non-trivial probabilistic
models based on the maximum entropy (MaxEnt) principle. We show how MaxEnt
models allow for the natural incorporation of prior information. Furthermore,
they satisfy a number of desirable properties of previously introduced
randomization approaches. Lastly, they also have the benefit that they can be
represented explicitly. We argue that our approach can be used for a variety of
data types. However, for concreteness, we have chosen to demonstrate it in
particular for databases and networks.Comment: Submitte
A cookbook for temporal conceptual data modelling with description logic
We design temporal description logics suitable for reasoning about temporal conceptual data models and investigate their computational complexity. Our formalisms are based on DL-Lite logics with three types of concept inclusions (ranging from atomic concept inclusions and disjointness to the full Booleans), as well as cardinality constraints and role inclusions. In the temporal dimension, they capture future and past temporal operators on concepts, flexible and rigid roles, the operators `always' and `some time' on roles, data assertions for particular moments of time and global concept inclusions. The logics are interpreted over the Cartesian products of object domains and the flow of time (Z,<), satisfying the constant domain assumption. We prove that the most expressive of our temporal description logics (which can capture lifespan cardinalities and either qualitative or quantitative evolution constraints) turn out to be undecidable. However, by omitting some of the temporal operators on concepts/roles or by restricting the form of concept inclusions we obtain logics whose complexity ranges between PSpace and NLogSpace. These positive results were obtained by reduction to various clausal fragments of propositional temporal logic, which opens a way to employ propositional or first-order temporal provers for reasoning about temporal data models
Prioritized Repairing and Consistent Query Answering in Relational Databases
A consistent query answer in an inconsistent database is an answer obtained
in every (minimal) repair. The repairs are obtained by resolving all conflicts
in all possible ways. Often, however, the user is able to provide a preference
on how conflicts should be resolved. We investigate here the framework of
preferred consistent query answers, in which user preferences are used to
narrow down the set of repairs to a set of preferred repairs. We axiomatize
desirable properties of preferred repairs. We present three different families
of preferred repairs and study their mutual relationships. Finally, we
investigate the complexity of preferred repairing and computing preferred
consistent query answers.Comment: Accepted to the special SUM'08 issue of AMA
- âŠ