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OWL Reasoning with WebPIE: Calculating the Closure of 100 Billion Triples [chapter]

Jacopo Urbani, Spyros Kotoulas, Jason Maassen, Frank van Harmelen, Henri Bal
2010 Lecture Notes in Computer Science  
Our solutions allow distributed computation of the closure of an RDF graph under the OWL Horst semantics.  ...  We have evaluated our approach using some real-world datasets (UniProt and LDSR, about 0.9-1.5 billion triples) and a synthetic benchmark (LUBM, up to 100 billion triples).  ...  Each node calculates the closure of its partition using a conventional reasoner and the results are merged.  ... 
doi:10.1007/978-3-642-13486-9_15 fatcat:uqzzpudchzhrxneqx547u73fqy

WebPIE: A Web-scale Parallel Inference Engine using MapReduce

Jacopo Urbani, Spyros Kotoulas, Jason Maassen, Frank Van Harmelen, Henri Bal
2012 Journal of Web Semantics  
We have evaluated our system using very large real-world datasets (Bio2RDF, LLD, LDSR) and the LUBM synthetic benchmark, scaling up to 100 billion triples.  ...  Our technique addresses the challenge of distributed reasoning through a set of algorithms which, combined, significantly increase performance.  ...  We have shown inference on a triple set which is one order of magnitude larger than reported anywhere (100 billion triples against 12 billion triples).  ... 
doi:10.1016/j.websem.2011.05.004 fatcat:7hifunbllrf25fastlqnkt6bvi

Large Scale Fuzzy pD * Reasoning Using MapReduce [chapter]

Chang Liu, Guilin Qi, Haofen Wang, Yong Yu
2011 Lecture Notes in Computer Science  
The experimental results show that the running time of our system is comparable with that of WebPIE, the state-of-the-art inference engine for scalable reasoning in pD * semantics.  ...  To the best of our knowledge, this is the first work to investigate how MapReduce can help to solve the scalability issue of fuzzy OWL reasoning.  ...  [12] ) have proved that MapReduce is a very efficient framework to handle the computation of the closure containing up to 100 billion triples under pD * semantics.  ... 
doi:10.1007/978-3-642-25073-6_26 fatcat:f5zqayakbrgmtmrbbvixssb3se

QueryPIE: Backward Reasoning for OWL Horst over Very Large Knowledge Bases [chapter]

Jacopo Urbani, Frank van Harmelen, Stefan Schlobach, Henri Bal
2011 Lecture Notes in Computer Science  
To the best of our knowledge, QueryPIE is the first reported backward-chaining reasoner for OWL Horst that efficiently scales to a billion triples.  ...  As a proof of concept, we have implemented a prototype called QueryPIE (Query Parallel Inference Engine), and we have tested its performance on different datasets of up to 1 billion triples.  ...  This work was partly supported by the LarKC project (EU FP7-215535) and by the COMMIT project.  ... 
doi:10.1007/978-3-642-25073-6_46 fatcat:o6zepb5y2rbznoo6rdtvy3mw7a

Reasoning with Large Scale Ontologies in Fuzzy pD* Using MapReduce

Chang Liu, Guilin Qi, Haofen Wang, Yong Yu
2012 IEEE Computational Intelligence Magazine  
[7] and [8] ) have proved that MapReduce [9] is a very efficient framework to handle the computation of the closure of a RDF graph containing up to 100 billion triples under RDFS and pD * semantics  ...  In [8] , they further extended their methods to handle OWL pD * fragment, and conducted experiment over a dataset containing 100 billion triples. VI.  ...  For this reason, we must store all of these vague sameAs triples and calculate the sameAs closure using rules f-rdfp6 and f-rdfp7 to ensure the inference is complete.  ... 
doi:10.1109/mci.2012.2188589 fatcat:swiitidb7nhp5jjiqlcyy3nv5q

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)  
We highlight the shortcomings of these approaches and discuss some of the open problems related to performing scalable reasoning.  ...  However, reasoning approaches need to be scalable in order to enable reasoning over the entire Web of Data.  ...  "III: Small: TROn -Tractable Reasoning with Ontologies."  ... 
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  
We highlight the shortcomings of these approaches and discuss some of the open problems related to performing scalable reasoning.  ...  However, reasoning approaches need to be scalable in order to enable reasoning over the entire Web of Data.  ...  "III: Small: TROn -Tractable Reasoning with Ontologies."  ... 
doi:10.1145/2611040.2611041 dblp:conf/wims/AntoniouBT14 fatcat:g3ljwx4eqrg3po242ckkv6rwme

High-Performance Computing Applied to Semantic Databases [chapter]

Eric L. Goodman, Edward Jimenez, David Mizell, Sinan al-Saffar, Bob Adolf, David Haglin
2011 Lecture Notes in Computer Science  
We show scaling up to 512 processors (the largest configuration we had available), and the ability to process 20 billion triples completely in-memory.  ...  that far surpass current state of the art.  ...  [6] perform RDFS closure on an RDF data set gathered from various sources on the web, and then later expand to a fragment of OWL reasoning on data sets ranging up to 100 billion triples [7] .  ... 
doi:10.1007/978-3-642-21064-8_3 fatcat:trvcbdgj6beghkcw6rqnkn5rx4

An unsupervised classification process for large datasets using web reasoning

Rafael Peixoto, Thomas Hassan, Christophe Cruz, Aurélie Bertaux, Nuno Silva
2016 Proceedings of the International Workshop on Semantic Big Data - SBD '16  
This paper focuses in the last two steps and presents a new highly scalable process to classify items from huge sets of unstructured text by using ontologies and rule-based reasoning.  ...  Determining valuable data among large volumes of data is one of the main challenges in Big Data.  ...  Web-Scale Reasoners based in Map-reduce programming model like WebPie [22] outperforms all other published approaches in an inference test over 100 billion triples [25] .  ... 
doi:10.1145/2928294.2928301 dblp:conf/sigmod/PeixotoHCBS16 fatcat:f6ina2i74rfmrpzk76z45wmrnu

FactForge: A fast track to the Web of data

Barry Bishop, Atanas Kiryakov, Damyan Ognyanov, Ivan Peikov, Zdravko Tashev, Ruslan Velkov
2011 Semantic Web Journal  
This Web application is based on OWLIM, a high performance semantic repository that offers outstanding RDF data management and reasoning capabilities based on OWL.  ...  This paper gives an overview of FactForge, its many unique capabilities and its role within the emerging trend for the exploitation of Linked Open Data using OWL-based inference.  ...  complexity to OWL Horst over datasets with a maximum size of between one and ten billion explicit statements.  ... 
doi:10.3233/sw-2011-0040 fatcat:b7c6zztuh5fhrhjjuf3bju4lfu

Hybrid reasoning on OWL RL

Jacopo Urbani, Robert Piro, Frank van Harmelen, Henri Bal
2014 Semantic Web Journal  
To the best of our knowledge our method is the first that demonstrates complex rule-based reasoning at query time over an input of several billion triples and it takes a step forward towards truly large-scale  ...  of our method to execute efficiently (most of) the OWL RL rules.  ...  of this article with a careful review of the work.  ... 
doi:10.3233/sw-130120 fatcat:2r4i2m7kqzb67niw7ep4d5l5o4

OWL Reasoning Framework over Big Biological Knowledge Network

Huajun Chen, Xi Chen, Peiqin Gu, Zhaohui Wu, Tong Yu
2014 BioMed Research International  
Recently, huge amounts of data are generated in the domain of biology. Embedded with domain knowledge from different disciplines, the isolated biological resources are implicitly connected.  ...  In this paper, we present a general OWL (web ontology language) reasoning framework to study the implicit relationships among biological entities.  ...  This work is funded by LY13F020005 of NSF of Zhejiang, NSFC61070156, YB2013120143, and Fundamental Research Funds for the Central Universities.  ... 
doi:10.1155/2014/272915 pmid:24877076 pmcid:PMC4022201 fatcat:qoa7rzhjevhyfc7trpmwi6424u

Scalable and distributed methods for entity matching, consolidation and disambiguation over linked data corpora

Aidan Hogan, Antoine Zimmermann, Jürgen Umbrich, Axel Polleres, Stefan Decker
2012 Journal of Web Semantics  
the feasibility of our methods at that scale, and giving insights into the quality of the results for real-world data.  ...  using OWL 2 RL/RDF rules.  ...  [57] present the LinksB2N system, which aims to perform scalable integration of RDF data, particularly focusing on evaluation over corpora from the marketing domain; however, their methods are not specific  ... 
doi:10.1016/j.websem.2011.11.002 fatcat:gekxu2bqarbt5h2mkbtpedbj5m

Scalable and Distributed Methods for Entity Matching, Consolidation and Disambiguation Over Linked Data Corpora

Aidan Hogan, Antoine Zimmermann, JJrgen Umbrich, Axel Polleres, Stefan Decker
2012 Social Science Research Network  
the feasibility of our methods at that scale, and giving insights into the quality of the results for real-world data.  ...  using OWL 2 RL/RDF rules.  ...  [57] present the LinksB2N system, which aims to perform scalable integration of RDF data, particularly focusing on evaluation over corpora from the marketing domain; however, their methods are not specific  ... 
doi:10.2139/ssrn.3198933 fatcat:rkewnbi6rvbyzj4zbczjkb2y5u

BigDataGrapes D4.2 - Methods and Tools for Distributed Inference

Milena Yankova, Boyan SImeonov, Atanas Kiryakov, Vladimir Alexiev
2020 Zenodo  
The Final section is dedicated to state of the art with standard theoretical approach to inference from descriptive logic stand point, as well as related work in implementing those approaches.  ...  There are many challenges in data reasoning and inference based on distributed data. The first one is addressing data security and access rights to both original data and inferred information.  ...  The result is the so-called inferred closure: an extension of a knowledge base (the RDF dataset or the graph of RDF triples) with all implicit facts (RDF triples) that can be inferred from it.  ... 
doi:10.5281/zenodo.4546071 fatcat:qwkhk7crvzgwvfz3dxzaqmy46m
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