A computational model for the integration of linked data in mobile augmented reality applications

A mobile query service for integrated access to large numbers of online semantic web data sources

“…On the other hand, since the number of cache units in Meta Cache is comparably much higher (due to the higher amount of distinct metadata combinations), we found that keeping separate AndroJena graphs per cache unit caused too much memory overhead 7 . Therefore, cache units in Meta Cache still keep their data as a string.…”

“…A retrieval unit keeps (pointers to) the data retrieved when accessing the %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%% 7 %A higher result value means the source is less likely to be…”

“…Various mobile computing domains currently leverage semantic data, including augmented reality [6,7], recommender systems [8], location-aware [9,10] and context-aware systems [11,12], mobile tourism [13] and m-Health [14]. Typically, these systems access online semantic data via SPARQL query endpoints.…”

Benchmarking semantic reasoning on mobile platforms: Towards optimization using OWL2 RL

“…Advances in mobile technologies have enabled mobile applications to consume semantic data, with the goal of e.g., collecting context- [52], [59] and location-related data [6], [50], achieving augmented reality [42], [58], performing recommendations [60], accessing linked biomedical data (m-Health) [40] and enabling mobile tourism [28]. Automated reasoning, an essential Semantic Web pillar, involves the inference of useful information based on the semantics of ontology constructs, domain-specific if-then rules, or both.…”