Answers Partitioning and Lazy Joins for Efficient Query Relaxation and Application to Similarity Search

• Published in: The Semantic Web Vol. 10843; pp. 209 - 224
• Main Author: Ferré, Sébastien
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2018; Springer International Publishing
• Series: Lecture Notes in Computer Science
• ISBN: 9783319934167; 3319934163
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-93417-4_14

Query relaxation has been studied as a way to find approximate answers when user queries are too specific or do not align well with the data schema. We are here interested in the application of query relaxation to similarity search of RDF nodes based on their description. However, this is challenging because existing approaches have a complexity that grows in a combinatorial way with the size of the query and the number of relaxation steps. We introduce two algorithms, answers partitioning and lazy join, that together significantly improve the efficiency of query relaxation. Our experiments show that our approach scales much better with the size of queries and the number of relaxation steps, to the point where it becomes possible to relax large node descriptions in order to find similar nodes. Moreover, the relaxed descriptions provide explanations for their semantic similarity.