Coincidence-Based Refinement of Ontology Matching

Since the beginning of the evolution of Semantic Web in the late 90's, many different aspects of it have received a great interest in both academy and technology. Alongside, because many problems get reduced to the problem of Ontology Matching, so many researches across the world have been devoted to this. Amongst these researches, one can find a variety of techniques employed for dealing with the problem. In all such techniques, there usually exist two different phases in coming to a to-be-proposed matching; Firstly, they come to an initial estimate for the similarity of the concepts involved. Secondly, based on certain criteria, they offer a (set of) matching(s). In this paper, we are about to present a new criteria for that final phase

Maintenance of Spatial Semijoin Queries on Moving Points

semijoin queries over continuously moving points, where points are modeled as linear functions of time. This is analogous to the maintenance of a materialized view except, as time advances, the query result may change independently of updates. As in a materialized view, we assume there is no prior knowledge of updates before they occur. We present a new approach, continuous fuzzy sets (CFS), to maintain continuous spatial semijoins efficiently. CFS is compared experimentally to a simple scaling of previous work