Three partition refinement algorithms
SIAM Journal on Computing
An implementation of an efficient algorithm for bisimulation equivalence
Science of Computer Programming
Data on the Web: from relations to semistructured data and XML
Data on the Web: from relations to semistructured data and XML
Covering indexes for branching path queries
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Index Structures for Path Expressions
ICDT '99 Proceedings of the 7th International Conference on Database Theory
DataGuides: Enabling Query Formulation and Optimization in Semistructured Databases
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Computing simulations on finite and infinite graphs
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
C-store: a column-oriented DBMS
VLDB '05 Proceedings of the 31st international conference on Very large data bases
An efficient SQL-based RDF querying scheme
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Scalable semantic web data management using vertical partitioning
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Efficient aggregation for graph summarization
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
RDF-3X: a RISC-style engine for RDF
Proceedings of the VLDB Endowment
Measuring the similarity of labeled graphs
ICCBR'03 Proceedings of the 5th international conference on Case-based reasoning: Research and Development
Querying the Data Web: The MashQL Approach
IEEE Internet Computing
Querying RDF data from a graph database perspective
ESWC'05 Proceedings of the Second European conference on The Semantic Web: research and Applications
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Companies, Communities, Research Labs, and even Governments are all competing on publishing structured data in the web in many forms such as RDF and XML. Many Datasets are now being published and linked together, including Wikipedia, Yago, DBLP, IEEE, IBM, Flickr, and US and UK government data. Most of these datasets are published in RDF which is a graph-based data model. However, querying RDF graphs is a major problem which has brought the attention of the research community. Among the many approaches proposed to tune up the performance of queries over data graphs, a number of them proposed to summarize RDF graphs for query optimization; instead of querying a dataset, queries are executed over the summary of the dataset. In order to summarize a dataset, two well known algorithms are being used, namely, Trace Equivalence and Bisimilarity. Nevertheless, these are memory based and thus suffer from scalability problems because of the limitations imposed by the memory. In this paper, we propose disk-based versions of those memory-based algorithms and we adapt them to RDF data. Our proposed algorithms are experimented on relatively large datasets and using different sizes of memory to prove that they are indeed disk based.