33,053 research outputs found
Space Efficiency of Propositional Knowledge Representation Formalisms
We investigate the space efficiency of a Propositional Knowledge
Representation (PKR) formalism. Intuitively, the space efficiency of a
formalism F in representing a certain piece of knowledge A, is the size of the
shortest formula of F that represents A. In this paper we assume that knowledge
is either a set of propositional interpretations (models) or a set of
propositional formulae (theorems). We provide a formal way of talking about the
relative ability of PKR formalisms to compactly represent a set of models or a
set of theorems. We introduce two new compactness measures, the corresponding
classes, and show that the relative space efficiency of a PKR formalism in
representing models/theorems is directly related to such classes. In
particular, we consider formalisms for nonmonotonic reasoning, such as
circumscription and default logic, as well as belief revision operators and the
stable model semantics for logic programs with negation. One interesting result
is that formalisms with the same time complexity do not necessarily belong to
the same space efficiency class
Ontological Foundations for Geographic Information Science
We propose as a UCGIS research priority the topic of “Ontological Foundations for Geographic Information.” Under this umbrella we unify several interrelated research subfields, each of which deals with different perspectives on geospatial ontologies and their roles in geographic information science. While each of these subfields could be addressed separately, we believe it is important to address ontological research in a unitary, systematic fashion, embracing conceptual issues concerning what would be required to establish an exhaustive ontology of the geospatial domain, issues relating to the choice of appropriate methods for formalizing ontologies, and considerations regarding the design of ontology-driven information systems. This integrated approach is necessary, because there is a strong dependency between the methods
used to specify an ontology, and the conceptual richness, robustness and tractability of the ontology itself. Likewise, information system implementations are needed as testbeds of the usefulness of every aspect of an exhaustive ontology of the geospatial domain. None of the current UCGIS research priorities provides such an integrative perspective, and therefore the topic of “Ontological Foundations for Geographic Information Science” is unique
The Need to Support of Data Flow Graph Visualization of Forensic Lucid Programs, Forensic Evidence, and their Evaluation by GIPSY
Lucid programs are data-flow programs and can be visually represented as data
flow graphs (DFGs) and composed visually. Forensic Lucid, a Lucid dialect, is a
language to specify and reason about cyberforensic cases. It includes the
encoding of the evidence (representing the context of evaluation) and the crime
scene modeling in order to validate claims against the model and perform event
reconstruction, potentially within large swaths of digital evidence. To aid
investigators to model the scene and evaluate it, instead of typing a Forensic
Lucid program, we propose to expand the design and implementation of the Lucid
DFG programming onto Forensic Lucid case modeling and specification to enhance
the usability of the language and the system and its behavior. We briefly
discuss the related work on visual programming an DFG modeling in an attempt to
define and select one approach or a composition of approaches for Forensic
Lucid based on various criteria such as previous implementation, wide use,
formal backing in terms of semantics and translation. In the end, we solicit
the readers' constructive, opinions, feedback, comments, and recommendations
within the context of this short discussion.Comment: 11 pages, 7 figures, index; extended abstract presented at VizSec'10
at http://www.vizsec2010.org/posters ; short paper accepted at PST'1
Simplification of UML/OCL schemas for efficient reasoning
Ensuring the correctness of a conceptual schema is an essential task in order to avoid the propagation of errors during software development. The kind of reasoning required to perform such task is known to be exponential for UML class diagrams alone and even harder when considering OCL constraints. Motivated by this issue, we propose an innovative method aimed at removing constraints and other UML elements of the schema to obtain a simplified one that preserve the same reasoning outcomes. In this way, we can reason about the correctness of the initial artifact by reasoning on a simplified version of it. Thus, the efficiency of the reasoning process is significantly improved. In addition, since our method is independent from the reasoning engine used, any reasoning method may benefit from it.Peer ReviewedPostprint (author's final draft
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