A logic programming framework for modeling temporal objects

We present a general approach for modeling temporal aspects of objects in a logic programming framework. Change is formulated in the context of a database which stores explicitly a record of all changes that have occurred to objects and thus (implicitly) all states of objects in the database. A snapshot of the database at any given time is an object-oriented database, in the sense that it supports an object-based data model. An object is viewed as a collection of simple atomic formulas, with support for an explicit notion of object identity, classes and inheritance. The event calculus is a treatment of time and change in first-order classical logic augmented with negation as failure. The paper develops a variant of the event calculus for representing changes to objects, including change in internal state of objects, creation and deletion of objects, acid mutation of objects over time. The concluding sections present two natural and straightforward extensions, to deal with versioning of objects and schema evolution, and a sketch of implementation strategies for practical application to temporal object-oriented databases.


A fuzzy deductive object-oriented database model
Bostan, B; Yazıcı, Adnan (1998-05-09)
Object-oriented and deductive database models are two different paradigms in database modeling. As has been pointed out by many researchers, [1], [6], [14], each of these data models has its shortcomings when dealing with database/knowledge-base applications. Therefore, it is believed that combining object-oriented concepts with those of deductive database modeling results in a powerful data model especially for knowledge-intensive applications. In these applications, it is important to model and manipulate...
Using fuzzy Petri nets for static analysis of rule-bases
Bostan-Korpeoglu, B; Yazıcı, Adnan (2004-01-01)
We use a Fuzzy Petri Net (FPN) structure to represent knowledge and model the behavior in our intelligent object-oriented database environment, which integrates fuzzy, active and deductive rules with database objects. However, the behavior of a system can be unpredictable due to the rules triggering or untriggering each other (non-termination). Intermediate and final database states may also differ according to the order of rule executions (non-confluence). In order to foresee and solve problematic behavior...
An Approach to manage variability in object-oriented applications with feature models
Bulut, Ender; Şener, Cevat; Department of Computer Engineering (2014)
In this thesis, an approach to manage variability in object-oriented applications by using a feature modeling language and a simple source code generation technique has been designed and developed. This approach provides developing configurable object oriented applications in a practical way. That is, an application developed with our approach takes just a configuration file including user selections in a pre-defined domain as input and then automatically configure and manage itself with respect to these se...
A probabilistic sparse skeleton based object detection
Altinoklu, Burak; Ulusoy, İlkay; Tarı, Zehra Sibel (Elsevier BV, 2016-11)
We present a Markov Random Field (MRF) based skeleton model for object shape and employ it in a probabilistic chamfer-matching framework for shape based object detection. Given an object category, shape hypotheses are generated from a set of sparse (coarse) skeletons guided by suitably defined unary and binary potentials at and between shape parts. The Markov framework assures that the generated samples properly reflect the observed or desired shape variability. As the model employs a sparsely sampled skele...
A fuzzy database and knowledge base environment for intelligent retrieval
Koyuncu, M; Yazıcı, Adnan (2001-07-28)
We discuss an environment that permits flexible modeling and fuzzy querying of complex data and knowledge including uncertainty. With such an environment, one can have intelligent retrieval of information from knowledge- intensive applications. In this study, we specifically describe the details (the model, inference mechanism, etc,) of the fuzzy knowledge base system (coupled with a fuzzy object-oriented database system, namely FOOD) of this environment.
Citation Formats
F. N. Çiçekli and M. Sergot, “A logic programming framework for modeling temporal objects,” IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, vol. 8, no. 5, pp. 724–741, 1996, Accessed: 00, 2022. [Online]. Available: https://hdl.handle.net/11511/100526.