In order to deal with the systematic verification with uncertain information in possibility
theory, Li and Li (2013) introduced model checking of linear-time properties in which the …

We present a real-time method for detecting deformable surfaces, with no need whatsoever
for a priori pose knowledge. Our method starts from a set of wide baseline point matches …

We live in the Information Age, where most of the personal, business, and administrative
data are collected and managed electronically. However, poor data quality may affect the …

Graph pattern matching is a hot spot in the big data era, which is to find answer graphs
matching a given query graph in a data graph of graph databases.“Matching” means two …

Currently, there is uncertainty in the modeling techniques of cyber-physical systems (CPS)
when faced with the multiple possibilities and distributions of complex system behavior. This …

Large amounts of data are collected by public administrations and healthcare organizations,
the integration of the data scattered in several information systems can facilitate the …

The paper introduces the Robust Data Quality Analysis which exploits formal methods to
support Data Quality Improvement Processes. The proposed methodology can be applied to …

Semantic Web applications meet a serious problem in practice: the shortage of semantic
data (ontologies). Since the vast majority of data are still stored in relational databases, they …

Data cleansing is growing in importance among both public and private organisations,
mainly due to the relevant amount of data exploited for supporting decision making …

To tackle the issues of semantic collision and inconsistencies between ontologies and the
original data model while learning ontology from relational database (RDB), a semi …