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Sum-Max Monotonic Ranked Joins for Evaluating Top-K Twig Queries on Weighted Data Graphs

9 years 7 months ago
Sum-Max Monotonic Ranked Joins for Evaluating Top-K Twig Queries on Weighted Data Graphs
In many applications, the underlying data (the web, an XML document, or a relational database) can be seen as a graph. These graphs may be enriched with weights, associated with the nodes and edges of the graph, denoting application specific desirability/penalty assessments, such as popularity, trust, or cost. A particular challenge when considering such weights in query processing is that results need to be ranked accordingly. Answering keyword-based queries on weighted graphs is shown to be computationally expensive. In this paper, we first show that answering queries with further structure imposed on them remains NP-hard. We next show that, while the query evaluation task can be viewed in terms of ranked structural-joins along query axes, the monotonicity property, necessary for ranked join algorithms, is violated. Consequently, traditional ranked join algorithms are not directly applicable. Thus, we establish an alternative, sum-max monotonicity property and show how to leverage...
Yan Qi 0002, K. Selçuk Candan, Maria Luisa
Added 09 Jun 2010
Updated 09 Jun 2010
Type Conference
Year 2007
Where VLDB
Authors Yan Qi 0002, K. Selçuk Candan, Maria Luisa Sapino
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