@conference {DBLP:conf/debs/ChantziosZST19,
	title = {Ping - A customizable, open-source information filtering system for textual data},
	booktitle = {Proceedings of the 13th ACM International Conference on Distributed and Event-based Systems, DEBS 2019, Darmstadt, Germany, June 24-28, 2019.},
	year = {2019},
	pages = {228{\textendash}231},
	doi = {10.1145/3328905.3332512},
	url = {https://doi.org/10.1145/3328905.3332512},
	author = {Thanasis Chantzios and Lefteris Zervakis and Spiros Skiadopoulos and Christos Tryfonopoulos}
}
@article {581,
	title = {Query Reorganisation Algorithms for Efficient Boolean Information Filtering},
	journal = {IEEE Transactions on Knowledge and Data Engineering},
	volume = {29},
	year = {2017},
	pages = {418{\textendash}432},
	abstract = {In the information filtering paradigm, clients subscribe to a server with continuous queries that express their information needs and get notified every time appropriate information is published. To perform this task in an efficient way, servers employ indexing schemes that support fast matches of the incoming information with the query database. Such indexing schemes involve (i) main-memory trie-based data structures that cluster similar queries by capturing common elements between them and (ii) efficient filtering mechanisms that exploit this clustering to achieve high throughput and low filtering times. However, state-of-the-art indexing schemes are sensitive to the query insertion order and cannot adopt to an evolving query workload, degrading the filtering performance over time. In this paper, we present an adaptive trie-based algorithm that outperforms current methods by relying on query statistics to reorganise the query database. Contrary to previous approaches, we show that the nature of the constructed tries, rather than their compactness, is the determining factor for efficient filtering performance. Our algorithm does not depend on the order of insertion of queries in the database, manages to cluster queries even when clustering possibilities are limited, and achieves more than 96\% filtering time improvement over its state-of-the-art competitors. Finally, we demonstrate that our solution is easily extensible to multi-core machines.},
	keywords = {dissemination, indexing methods, Information filtering, user profiles and alert services},
	doi = {10.1109/TKDE.2016.2620140},
	url = {https://doi.org/10.1109/TKDE.2016.2620140},
	author = {Lefteris Zervakis and Christos Tryfonopoulos and Spiros Skiadopoulos and Manolis Koubarakis}
}
@conference {DBLP:conf/esws/ZervakisTSK16,
	title = {Full-Text Support for Publish/Subscribe Ontology Systems},
	booktitle = {The Semantic Web. Latest Advances and New Domains - 13th International Conference, ESWC 2016, Heraklion, Crete, Greece, May 29 - June 2, 2016, Proceedings},
	year = {2016},
	pages = {233{\textendash}249},
	doi = {10.1007/978-3-319-34129-3_15},
	url = {https://doi.org/10.1007/978-3-319-34129-3_15},
	author = {Lefteris Zervakis and Christos Tryfonopoulos and Spiros Skiadopoulos and Manolis Koubarakis}
}
@conference {DBLP:conf/edbt/ZervakisTSSS16,
	title = {Towards Publish/Subscribe Functionality on Graphs},
	booktitle = {Proceedings of the Workshops of the EDBT/ICDT 2016 Joint Conference, EDBT/ICDT Workshops 2016, Bordeaux, France, March 15, 2016.},
	year = {2016},
	url = {http://ceur-ws.org/Vol-1558/paper13.pdf},
	author = {Lefteris Zervakis and Christos Tryfonopoulos and Vinay Setty and Stephan Seufert and Spiros Skiadopoulos}
}
@conference {563,
	title = {Cloud-Based Data and Knowledge Management for Multi-Centre Biomedical Studies},
	booktitle = {Proceedings of the International Conference on Knowledge Capture (K-CAP)},
	year = {2015},
	month = {October 7-10},
	address = {Palisades NY, USA},
	abstract = {Among the basic research tools for (bio)medical science are epidemiological studies that typically involve a number of hospitals, clinics, and research centres scattered around the world, and are often referred to as multi-centre studies. Clearly, the effectiveness and importance of a multi-centre study increases with the number of participating centres and enrolled patients, but at the same time this natural distribution in the production of research data requires sophisticated data management infrastructures to support the participating units. This kind of infrastructure is not only expensive to build and maintain, but also cannot be reused as it is often tailored to a specific study. In this work, we present a cloud-based system, coined CLOUDSTUDY, that allows users without any computer science background to design, deploy, and administer platforms aimed for managing, sharing, and analysing clinical data from multi-centre studies. The CLOUDSTUDY system provides a zero-administration, zero-cost online tool for creating multi- centre studies that (i) enhances re-usability by introducing study templates, (ii) supports (bio)medical needs through specialised data types, and (iii) emphasises data filtering/export through an expressive yet simple graphical query engine.},
	doi = {10.1145/2815833.2816949},
	url = {https://doi.org/10.1145/2815833.2816949},
	author = {Amalia Tsafara and Christos Tryfonopoulos and Spiros Skiadopoulos and Lefteris Zervakis}
}
@conference {DBLP:conf/kcap/TsafaraTSZ15,
	title = {Cloud-Based Data and Knowledge Management for Multi-Centre Biomedical Studies},
	booktitle = {Proceedings of the 8th International Conference on Knowledge Capture, K-CAP 2015, Palisades, NY, USA, October 7-10, 2015},
	year = {2015},
	pages = {24:1{\textendash}24:4},
	doi = {10.1145/2815833.2816949},
	url = {https://doi.org/10.1145/2815833.2816949},
	author = {Amalia Tsafara and Christos Tryfonopoulos and Spiros Skiadopoulos and Lefteris Zervakis}
}
@article {DBLP:journals/corr/ZervakisTPKS13,
	title = {Full-text Support for Publish/Subscribe Ontology Systems},
	journal = {CoRR},
	volume = {abs/1307.2015},
	year = {2013},
	url = {http://arxiv.org/abs/1307.2015},
	author = {Lefteris Zervakis and Christos Tryfonopoulos and Antonios Papadakis-Pesaresi and Manolis Koubarakis and Spiros Skiadopoulos}
}
@conference {554,
	title = {Full-text Support for Publish/Subscribe Ontology Systems},
	booktitle = {Proceedings of the Extended Semantic Web Conference (ESWC)},
	year = {2012},
	month = {May},
	address = {Crete, Greece},
	author = {Lefteris Zervakis and Christos Tryfonopoulos and Antonios Papadakis-Pesaresi and Manolis Koubarakis and Spiros Skiadopoulos}
}
