Comparison of access methods for time-evolving data
ACM Computing Surveys (CSUR)
Temporal and Real-Time Databases: A Survey
IEEE Transactions on Knowledge and Data Engineering
Change-Centric Management of Versions in an XML Warehouse
Proceedings of the 27th International Conference on Very Large Data Bases
Semantic Data Caching and Replacement
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
ACM Transactions on Database Systems (TODS)
Graphs over time: densification laws, shrinking diameters and possible explanations
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
IEEE Transactions on Knowledge and Data Engineering
On the evolution of user interaction in Facebook
Proceedings of the 2nd ACM workshop on Online social networks
Pregel: a system for large-scale graph processing
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
PEGASUS: mining peta-scale graphs
Knowledge and Information Systems - Special Issue: Best Papers of the Fifth International Conference on Advanced Data Mining and Applications (ADMA 2009)
GBASE: a scalable and general graph management system
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Ego-centric Graph Pattern Census
ICDE '12 Proceedings of the 2012 IEEE 28th International Conference on Data Engineering
Query processing under GLAV mappings for relational and graph databases
Proceedings of the VLDB Endowment
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In this paper, we deal with the problem of historical query evaluation over evolving social graphs. Historical queries are queries about the social graph in the past. The straightforward way of executing such a query is by first reconstructing the whole social graph at the given time instance or interval, and then, evaluating the query on the reconstructed graph. Since social graphs are large, the cost of a complete graph snapshot reconstruction would dominate the cost of historical query execution. Given that many queries are user-centric, i.e., node-centric queries that require access only of a targeted subgraph, we propose deploying partial view instead of full snapshot construction and define conditions that determine when a partial view can be used to evaluate a query. We also propose using a cache of partial views to further reduce the query evaluation cost, and show how partial views can be extended to new views with reduced cost. Finally, we present a greedy solution for the static view selection problem and study its performance experimentally.