Spatial Search in Large RDF Knowledge Bases


In this talk, I will present our recent work on indexing spatial information in RDF knowledge bases in order to facilitate efficient spatial search. The RDF data model has recently been extended to support representation and querying of spatial information (i.e., locations and geometries) associated with RDF entities. Still, there are limited efforts towards extending RDF stores to efficiently support spatial search. Our first contribution in this direction is an effective encoding scheme for entities having spatial locations, paired with the introduction of on-the-fly spatial filters and spatial join algorithms, and several optimizations that minimize the overhead of geometry and dictionary accesses. We implemented the proposed techniques as an extension to the open-source RDF-3X engine and we experimentally evaluated them using real RDF knowledge bases. The results show that our system offers robust performance for spatial queries, while introducing little overhead to the original query engine. Our second contribution is the introduction of spatial RDF keyword queries, which enable users to express their search needs without having to know structured query languages, such as SPARQL and the RDF schema. The user only inputs a set of keywords and the goal is to find small RDF subgraphs which contain all keywords, centered at a node which is spatially located near the user. We design a basic method for the processing of such queries. To further accelerate retrieval, two pruning approaches and a data pre-processing technique are proposed. Our empirical studies on two real datasets demonstrate the effectiveness and efficiency of our approaches.


Prof. Nikos MAMOULIS
University of Hong Kong
Hong Kong

Date & Time

9 Dec 2016 (Friday) 16:00 - 17:00


E11-4045 (University of Macau)

Organized by

Department of Computer and Information Science


Nikos Mamoulis received a diploma in Computer Engineering and Informatics in 1995 from the University of Patras, Greece, and a PhD in Computer Science in 2000 from the Hong Kong University of Science and Technology. He is currently a professor at the Department of Computer Science, University of Hong Kong, which he joined in 2001. His research focuses on the management and mining of complex data types, including spatial, spatio-temporal, object-relational, multimedia, text and semi-structured data. He has published more than 150 articles in conferences and journals of database research. He has served on the program committees of over 100 international conferences and workshops on data management and data mining. He was the general chair of SSDBM 2008 and the PC chair of SSTD 2009. He served as associate editor for IEEE TKDE and he's currently serving as associate editor for VLDBJ and KAIS. He received the Outstanding Young Researcher Award from HKU in 2009 and the best paper award of SSTD 2015.