, They may focus on the whole graph or a part of it. Summaries have been used to support indexing and query processing, that is, allow a query to be partially or fully evaluated on the smaller summary instead of G. They can also be used as a static analysis tool, e.g., to detect empty-answer queries without actually consulting G. In this work, we study structural quotient summaries, which are complete and representative as discussed in Section 2.2. Quotient summaries most widely studied in the literature are based on bisimulation, They may rely on graph structure, graph values or graph statistics
, Other types of summaries, such as Dataguides [19] are not quotients, as a graph node may be represented by more than one node. A Dataguide may be larger than the original graph, and its construction has worst-case exponential time complexity in the size of G. With a focus farther from our work, [11] introduces an aggregation framework for OLAP on labeled graphs, while we focus on representing complete graph structure and semantics. [10] builds a set of randomized summaries to be mined instead of the original graph for better performance, with guaranteed bounds on the information loss. Focusing on RDF graphs, Bisimulation-and clique-based summaries each have distinct advantages, and can be used side-by-side for different purposes. With respect to distributed way of computing the summaries
, Summaries based on clustering [21], user-defined aggregation rules [35], mining [10], and identification of frequent subtrees [40] are not complete and/or require user input. [33] introduces a simulation RDF quotient based on triple (not node) equivalence. [3] studies simple methods for summarizing D G , i.e. the data triples only. We had demonstrated [6] and (informally) presented G W and G TW in a short, However, these summaries ignore RDF saturation, and thus its interaction with summarization
, we propose a type-first summarization technique which exploits subclass hierarchies; beyond the quotient summary framework which it shares
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