In this paper we focus on the semantic heterogeneity problem as one of the main challenges in current Spatial Data Infrastructures (SDIs). We first report on the state of the art in reducing such a heterogeneity in SDIs. We then consider a particular geo-service integration scenario. We discuss an approach of how to semantically coordinate geographic services, which is based on a view of the se...

The requirement for ubiquitous service access in wireless environments presents a great challenge in light of well-known problems like high error rate and frequent disconnections. In order to satisfy this requirement, we propose the integration of two modern service technologies: Web Services and Mobile Agents. This integration allows wireless users to access and invoke semantically enriched We...

AutoTutor uses conversational intelligent agents in learning environments. One of the major challenges in developing AutoTutor applications is to assess students’ natural language answers to AutoTutor questions. We investigated an AutoTutor dataset with 3358 student answers to 49 AutoTutor questions. In comparisons with human ratings, we found that semantic matching works well for some question...

In this paper, we introduce a model analysis approach suitable for multiple analysis purposes. The approach is based on generic graph pattern matching and semantic standardization of model elements. Due to its generic nature, it is applicable to conceptual models of any graph-based modelling technique. Through semantic standardization, the approach relies on unambiguous model contents. Therefor...

The problem of nding meaningful subcircuits in a logic layout appears in many contexts in computer-aided design. Existing techniques rely upon nding exact matchings of subcircuit structure within the layout. These syntactic techniques fail to identify functionally equivalent subcircuits that are diierently implemented, optimized, or otherwise obfuscated. We present a mechanism for identifying f...

We view match as an operator that takes two graph-like structures (e.g., classifications, XML schemas) and produces a mapping between the nodes of these graphs that correspond semantically to each other. Semantic matching is based on two ideas: (i) we discover mappings by computing semantic relations (e.g., equivalence, more general); (ii) we determine semantic relations by analyzing the meanin...