1.

Context aware exception handling in business process execution language

We describe a novel context-aware architecture for fault handling in executable process, which enables dynamic fault handling during process execution.

COBISS.SI-ID: 9956436

2.

The role of Hubness in clustering high-dimensional data

We take a novel perspective on the problem of clustering high-dimensional data. Instead of attempting to avoid the curse of dimensionality by observing a lower dimensional feature subspace, we embrace dimensionality by taking advantage of inherently high-dimensional phenomena.

COBISS.SI-ID: 26713639

3.

General context-aware data matching and merging framework

The framework employs collective entity resolution and redundancy elimination using three dimensions of context types. In order to achieve domain independent results, data is enriched with semantics and trust. We introduce additional attribute, relationship, semantic and trust metrics, which allow complete framework management.

COBISS.SI-ID: 9735764