Despite the large volume of work on querying large RDF knowledge bases, only a few studies efficiently address spatial semantics in RDF data; existing initiatives mainly focus on supporting GeoSPARQL features with external spatial indices like the R-tree, and less on performance optimization. Our work proposed a number of techniques that can be applied to RDF engines in order to efficiently support spatial queries such as range selections and spatial joins. As a proof of concept, the proposed techniques were implemented inside the RDF-3X open-source store. Our key contribution of is an effective encoding scheme that encodes spatial approximations inside the identifiers of RDF entities with spatial locations and geometries. This scheme allows us to apply online cheap filters and spatial join algorithms without accessing the exact geometries of the involved entities.
- John Liagouris, Nikos Mamoulis, Panagiotis Bouros and Manolis Terrovitis:
An Effective Encoding Scheme for Spatial RDF Data
Proceedings of the VLDB Endowment (PVLDB), Vol 7, No 12, August 2014
The growth of Location-aware Social Networks (LASN) is unprecedented; given that users in LASNs such as Foursquare can rate venues, make recommendations and advertise interesting events, the economic importance and the potential impact of LASNs for businesses become apparent. Motivated by word-of-mouth and viral marketing campaigns, our work introduced the task of identifying the top-k Regionally Influential LASN Users (k-RIL). For example, an organizer of a city-wide festival is recruiting the most influential users within each district to locally advertise the festival. To solve k-RIL, we first proposed a novel propagation model and designed a methodology for computing the influence power of a user based on closeness centrality at the social graph. Then, we devised evaluation algorithms that examine candidate users in the order of their expected influence.
- Panagiotis Bouros, Dimitris Sacharidis and Nikos Bikakis:
Regionally Influential Users in Location-Aware Social Networks
Proceeding of the 22nd ACM International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL), Dallas, Texas, USA, November 4-7, 2014
Hierarchical structures such as topic directories are a popular way to organize information on the Web. In this context, we investigated the role of paths as knowledge artifacts; in particular, we proposed models to represent topic directories and a query language to manipulate path-like patterns together with raw data. Further, we studied the personlization of Web directories by mining user navigation patterns. For this purpose, we presented techniques for discovering group of users who exhibit similar navigation behaviour, termed interest groups. Essentially, the proposed personalization tasks aim at creating links termed shortcuts, between categories in the directory.
- Theodore Dalamagas, Panagiotis Bouros, Theodore Galanis, Magdalini Eirinaki and Timos Sellis:
Mining User Navigation Patterns for Personalizing Topic Directories
Proceedings of the 9th ACM CIKM International Workshop on Web Information and Data Management (WIDM), Lisbon, Portugal, November 9, 2007
- Aggeliki Koukoutsaki, Theodore Dalamagas, Timos Sellis and Panagiotis Bouros:
PatMan: A Visual Database System to Manipulate Path Patterns and Data in Hierarhical Catalogs
Proceedings of the International Workshop of the EU Network of Excellence DELOS on Audio-Visual Content and Information Visualization in Digital Libraries (AVIVDiLib), Cortona, Italy, May 4-6, 2005
- Panagiotis Bouros, Theodore Dalamagas, Timos Sellis and Manolis Terrovitis:
PatManQL: A language to manipulate patterns and data in hierarchical catalogs
Proceedings of the EDBT International Workshop on Pattern Representation and Management (PaRMa), Heraklion, Crete, Greece, March 18, 2004
- Panagiotis Bouros:
Query Language for Hierarchical Structures (in greek)
Diploma thesis, School of Electrical and Computer Engineering, National Technical University of Athens, Greece, 2003