Intensional Associations in Dataspaces

Dataspace applications necessitate the creation of associations among data items over time. For example, once information about people is extracted from sources on the Web, associations among them may emerge as a consequence of different criteria, such as their city of origin or their elected hobbies. In this paper, we advocate a declarative approach to specifying these associations. We propose that each set of associations be defined by an association trail. An association trail is a query-based definition of how items are connected by intensional (i.e., virtual) association edges to other items in the dataspace. We study the problem of processing neighborhood queries over such intensional association graphs. The naive approach to neighborhood query processing over intensional graphs is to materialize the whole graph and then apply previous work on dataspace graph indexing to answer queries. We present in this paper a novel indexing technique, the grouping-compressed index (GCI), that...

• Type: Conference
• Year: 2010
• Where: ICDE
• Authors: Marcos Antonio Vaz Salles, Jens Dittrich, Lukas Blunschi
• Keywords: Database, Dataspace Graph Indexing, ICDE 2010, Naive Approach, Worst-case Indexing Cost