A Generic Ontology Framework for Indexing Keyword Search on Massive Graphs (Extended Abstract)
Jiaxin Jiang, Byron Koon Kau Choi, Jianliang Xu, Sourav Saha Bhowmick · 2021
Due to the unstructuredness and the lack of schema information of knowledge graphs, social networks and RDF graphs, keyword search has been proposed for querying such graphs/networks. Recently, various keyword search semantics have been designed. In this work, we propose a generic ontologybased indexing framework for keyword search, called Bisimulation of Generalized Graph Index (BiG-index), to enhance the search performance. Novelties of BiG-index reside in using an ontology graph GOnt to summarize and index a data graph G iteratively, to form a hierarchical index structure G. BiG-index is generic since it is applicable to keyword search algorithms that have two properties. BiG-index reduced the runtimes of popular keyword search work Blinks by 50.5% and r-clique by 29.5%.