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Efficient Model Construction for Horn Logic with VLog [chapter]

Jacopo Urbani, Markus Krötzsch, Ceriel Jacobs, Irina Dragoste, David Carral
2018 Lecture Notes in Computer Science  
As our main contribution, we extend the in-memory Datalog engine VLog [11] to support Horn existential rules without equality (a fragment that encompasses Horn-SRI in terms of expressivity).  ...  Horn ontologies consisting of existential rules are used in various fields ranging from reasoning over knowledge graphs [7] and Description Logics (DL) ontologies [5, 6] , to data integration [4] and social  ...  Memory usage (left) and materialisation time (right) for VLog and RDFox for the restricted chase same rule sets.  ... 
doi:10.1007/978-3-319-94205-6_44 fatcat:ceirdsuqkne2beituhy4eyyhq4

Column-Oriented Datalog Materialization for Large Knowledge Graphs (Extended Technical Report) [article]

Jacopo Urbani, Ceriel Jacobs, Markus Krötzsch
2016 arXiv   pre-print
The evaluation of Datalog rules over large Knowledge Graphs (KGs) is essential for many applications.  ...  In this paper, we present a new method of materializing Datalog inferences, which combines a column-based memory layout with novel optimization methods that avoid redundant inferences at runtime.  ...  Introduction Knowledge graphs (KGs) are widely used in industry and academia to represent large collections of structured knowledge.  ... 
arXiv:1511.08915v2 fatcat:fnoxuh73lfabng676hdhjvbfja

Adaptive Low-level Storage of Very Large Knowledge Graphs [article]

Jacopo Urbani, Ceriel Jacobs
2020 arXiv   pre-print
The increasing availability and usage of Knowledge Graphs (KGs) on the Web calls for scalable and general-purpose solutions to store this type of data structures.  ...  We propose Trident, a novel storage architecture for very large KGs on centralized systems.  ...  We would like to thank (in alphabetical order) Peter Boncz, Martin Kersten, Stefan Manegold, and Gerhard Weikum for discussing and providing comments to improve this work.  ... 
arXiv:2001.09078v1 fatcat:thbu2agwj5ae7nwtuarfrbxeai

Adaptive Low-level Storage of Very Large Knowledge Graphs

Jacopo Urbani, Ceriel Jacobs
2020 Proceedings of The Web Conference 2020  
The increasing availability and usage of Knowledge Graphs (KGs) on the Web calls for scalable and general-purpose solutions to store this type of data structures.  ...  We propose Trident, a novel storage architecture for very large KGs on centralized systems.  ...  We would like to thank (in alphabetical order) Peter Boncz, Martin Kersten, Stefan Manegold, and Gerhard Weikum for discussing and providing comments to improve this work.  ... 
doi:10.1145/3366423.3380246 dblp:conf/www/UrbaniJ20 fatcat:pryxyqw2ovhetbgjfa5hmdgq5u

Beyond the Grounding Bottleneck: Datalog Techniques for Inference in Probabilistic Logic Programs

Efthymia Tsamoura, Victor Gutierrez-Basulto, Angelika Kimmig
2020 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
We propose an alternative approach that uses efficient Datalog techniques to integrate knowledge compilation with forward reasoning with a non-ground program.  ...  This effectively eliminates the grounding bottleneck that so far has prohibited the application of probabilistic logic programming in query answering scenarios over knowledge graphs, while also providing  ...  As VLog is a Datalog engine, we cannot directly use the rules as introduced in Section 3.  ... 
doi:10.1609/aaai.v34i06.6591 fatcat:pdmadpnohzch3oplbd7md7o7xm

A survey of large-scale reasoning on the Web of data

Grigoris Antoniou, Sotiris Batsakis, Raghava Mutharaju, Jeff Z. Pan, Guilin Qi, Ilias Tachmazidis, Jacopo Urbani, Zhangquan Zhou
2018 Knowledge engineering review (Print)  
In order to provide a first complete overview of the field, this paper reports a systematic review of such scalable reasoning approaches over various ontological languages, reporting details about the  ...  This is particularly true for the so-called Web of Data, in which data is semantically enriched and interlinked using ontologies.  ...  Part of this work was done by Raghava Mutharaju when he was a PhD student at Wright State University during which time he acknowledges the support of the National Science Foundation under award 1017225  ... 
doi:10.1017/s0269888918000255 fatcat:bergc5uphbceznigppektgvzrm

Large-Scale Reasoning with (Semantic) Data

Grigoris Antoniou, Sotiris Batsakis, Ilias Tachmazidis
2014 Proceedings of the 4th International Conference on Web Intelligence, Mining and Semantics (WIMS14) - WIMS '14  
In order to provide a first complete overview of the field, this paper reports a systematic review of such scalable reasoning approaches over various ontological languages, reporting details about the  ...  This is particularly true for the so-called Web of Data, in which data is semantically enriched and interlinked using ontologies.  ...  Part of this work was done by Raghava Mutharaju when he was a PhD student at Wright State University during which time he acknowledges the support of the National Science Foundation under award 1017225  ... 
doi:10.1145/2611040.2611041 dblp:conf/wims/AntoniouBT14 fatcat:g3ljwx4eqrg3po242ckkv6rwme

Pointing gestures in video blogs

Maximiliane Frobenius
2013 Text & Talk  
Pointing gestures are part of the resources that the medium affords to design vlogs for the absent recipients.  ...  Based on a corpus of 40 vlogs, this research categorizes different kinds of common pointing actions in vlogs.  ...  TED stands for Technology, Engineering, and Design Even more drastically different from vlogs is the reception situation of TED Talks.  ... 
doi:10.1515/text-2013-0001 fatcat:qggk6tslfzadjda2on7erwg5ei

Beyond the Grounding Bottleneck: Datalog Techniques for Inference in Probabilistic Logic Programs (Technical Report) [article]

Efthymia Tsamoura, Victor Gutierrez-Basulto, Angelika Kimmig
2019 arXiv   pre-print
We propose an alternative approach that uses efficient Datalog techniques to integrate knowledge compilation with forward reasoning with a non-ground program.  ...  This effectively eliminates the grounding bottleneck that so far has prohibited the application of probabilistic logic programming in query answering scenarios over knowledge graphs, while also providing  ...  As VLog is a Datalog engine, we cannot directly use the rules as introduced in Section 3.  ... 
arXiv:1911.07750v1 fatcat:r7akzemdajd3zhiadzqetc2tcq

DaRLing: A Datalog rewriter for OWL 2 RL ontological reasoning under SPARQL queries

ALESSIO FIORENTINO, JESSICA ZANGARI, MARCO MANNA
2020 Theory and Practice of Logic Programming  
AbstractThe W3C Web Ontology Language (OWL) is a powerful knowledge representation formalism at the basis of many semantic-centric applications.  ...  To fill the gap, we present DaRLing, a freely available Datalog rewriter for OWL 2 RL ontological reasoning under SPARQL queries.  ...  DaRLing also allows for Datalog translation of SPARQL queries containing basic graph patterns (BGPs) (i.e., sets of triple patterns forming a graph).  ... 
doi:10.1017/s1471068420000204 fatcat:diybvoxg3rdjtcvc3snryx7lti

An Integrated Framework for Sensing Radio Frequency Spectrum Attacks on Medical Delivery Drones [article]

Philip H. Kulp, Nagi Mei
2020 arXiv   pre-print
A detection framework capable of sensing attacks on drones could provide the capability for active responses.  ...  A gap exists in the literature for solo or swarm-based drones to identify radio frequency spectrum attacks.  ...  The analytic engine could be based on knowledge graphs and leverage the design of vlog (Carral et al., 2019) .  ... 
arXiv:2005.01503v1 fatcat:aoryteznyjhiflrrs6dcpdi2nu

DaRLing: A Datalog rewriter for OWL 2 RL ontological reasoning under SPARQL queries [article]

Alessio Fiorentino, Jessica Zangari, Marco Manna
2020 arXiv   pre-print
The W3C Web Ontology Language (OWL) is a powerful knowledge representation formalism at the basis of many semantic-centric applications.  ...  To fill the gap, we present DaRLing, a freely available Datalog rewriter for OWL 2 RL ontological reasoning under SPARQL queries.  ...  RDF DaRLing also allows for Datalog translation of SPARQL queries containing basic graph patterns (BGPs) (i.e., sets of triple patterns forming a graph).  ... 
arXiv:2008.02232v1 fatcat:s56tbm6rnnbxfi3tu7f56yb73u

Sentiment Analysis and Classification for Product Review in Social Networks

Selvaraj K, M. Muthu Madhavan
2017 IJARCCE  
for classify the extracted data's in a opinion mining.  ...  Then, we use these rules to extract candidate feature-opinion pairs directly.  ...  Feature Opinion The knowledge resource is useful for improving the performance of the opinion mining.  ... 
doi:10.17148/ijarcce.2017.6446 fatcat:smxdoujfxrgbjgsbrp264pb5gi

Blended Learning: An Effective Tool to Teach Presentation Skills

2019 International Journal of Engineering and Advanced Technology  
Therefore, looking for a more individualistic, change-oriented and opinionated individual.  ...  The paper is a study on engineering students following the strict timeline of the academic calendar, to deduce if it is an achievable target to develop student interest and level up their performance in  ...  The most common electronic tools presently used are various apps for collaboration and social networking websites, wikis, vlogs, multimedia instructions, webinars etc.  ... 
doi:10.35940/ijeat.a9448.109119 fatcat:hixfm4eyf5g6foauha7gtf4bq4

Scaling-up reasoning and advanced analytics on BigData

TYSON CONDIE, ARIYAM DAS, MATTEO INTERLANDI, ALEXANDER SHKAPSKY, MOHAN YANG, CARLO ZANIOLO
2018 Theory and Practice of Logic Programming  
This paper is under consideration for acceptance in Theory and Practice of Logic Programming.  ...  AbstractBigDatalog is an extension of Datalog that achieves performance and scalability on both Apache Spark and multicore systems to the point that its graph analytics outperform those written in GraphX  ...  Acknowledgements We would like to thank the reviewers for the comments and suggested improvements.  ... 
doi:10.1017/s1471068418000418 fatcat:xvfcjy4fi5ctvpesstdhqrhsvq
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