Theoretical Information Reuse and Integration

Information Reuse and Integration addresses the efficient extension and creation of knowledge through the exploitation of Kolmogorov complexity in the extraction and application of domain symmetry. Knowledge, which seems to be novel, can more often than not be recast as the image of a sequence of transformations, which yield symmetric knowledge. When the size of those transformations and/or the length of that sequence of transforms exceeds the size of the image, then that image is said to be novel or random. It may also be that the new knowledge is random in that no such sequence of transforms, which produces it exists, or is at least known.

The nine chapters comprising this volume incorporate symmetry, reuse, and integration as overt operational procedures or as operations built into the formal representations of data and operators employed. Either way, the aforementioned theoretical underpinnings of information reuse and integration are supported.

Latest research on Formal Methods Integration Best papers of the IEEE International Workshop on Formal Methods Integration - IEEE FMi 2015, held at San Francisco, USA, August 13-15 2015 Written by experts in the field Includes supplementary material: sn.pub/extras

Inhalt
Reuse and integration of specification logics: the hybridisation perspective.- Test Reactive Systems with Büchi-Automaton-Based Temporal Requirements.- Capturing and Verifying Dynamic Systems Behavior Using UML and -calculus.- A Real-time Concurrent Constraint Calculus for Analyzing Avionic Systems Embedded in the IMA Connected Through TTEthernet.- Case Indexing by Component, Context and Encapsulation for Knowledge Reuse.- Intelligent Decision Making for Customer Dynamics Management Based on Rule Mining and Contrast Set Mining A Segmentation Analysis Perspective.- Is Data Sampling Required When Using Random Forest for Classification on Imbalanced Bioinformatics Data?.- Concurrent Alignment of Multiple Anonymized Social Networks with Generic Stable Matching.- An Accurate Multi-sensor Multi-target Localization Method for Cooperating Vehicles.