资 源 简 介
A self-punctuating, horizon-based ranked join (HR-Join) operator is developed for ranked twig-query execution on data graphs, through leveraging sum-max monotonicity property of Join operations.
Abstract
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.
We establish an alternative, sum-max monotonicity property and show how to leverage this for developing a self-punctuating, horizon based ranked join (HR-Join) operator for ranked twig-query execution on data graphs.
