Paper Info
Title
FedSearch: Efficiently Combining Structured Queries and Full-Text Search in a SPARQL Federation
Abstract
Combining structured queries with full-text search provides a powerful means to access distributed linked data. However, executing hybrid search queries in a federation of multiple data sources presents a number of challenges due to data source heterogeneity and lack of statistical data about keyword selectivity. To address these challenges, we present FedSearch — a novel hybrid query engine based on the SPARQL federation framework FedX. We extend the SPARQL algebra to incorporate keyword search clauses as first-class citizens and apply novel optimization techniques to improve the query processing efficiency while maintaining a meaningful ranking of results. By performing on-the-fly adaptation of the query execution plan and intelligent grouping of query clauses, we are able to reduce significantly the communication costs making our approach suitable for top-k hybrid search across multiple data sources. In experiments we demonstrate that our optimization techniques can lead to a substantial performance improvement, reducing the execution time of hybrid queries by more than an order of magnitude.
Year
DOI
Venue
2013
10.1007/978-3-642-41335-3_27
International Semantic Web Conference (1)
Field
DocType
Volume
Data source,Web search query,Data mining,Information retrieval,Ranking,Computer science,Full text search,Linked data,SPARQL,Database,Query plan,Performance improvement
Conference
8218
ISSN
Citations 
PageRank 
0302-9743
4
0.42
References 
Authors
23
3
Name
Order
Citations
PageRank
Andriy Nikolov176953.09
Andreas Schwarte230315.59
Christian Hütter3252.81