Filters








113 Hits in 2.9 sec

Datalog Reasoning over Compressed RDF Knowledge Bases

Pan Hu, Jacopo Urbani, Boris Motik, Ian Horrocks
2019 Proceedings of the 28th ACM International Conference on Information and Knowledge Management - CIKM '19  
We present a novel materialisation technique that compresses the RDF triples so that the rules can sometimes be applied to multiple facts at once, and the derived facts can be represented using structure  ...  Materialisation is often used in RDF systems as a preprocessing step to derive all facts implied by given RDF triples and rules.  ...  Datalog applications typically require answering queries over facts derived from knowledge bases (KBs) encoded on the Web using the RDF [10] data model.  ... 
doi:10.1145/3357384.3358147 dblp:conf/cikm/HuUMH19 fatcat:lthj5zzlgzbwvkrvbhuyydxqqm

D2R2: Disk-Oriented Deductive Reasoning in a RISC-Style RDF Engine [chapter]

Mohamed Yahya, Martin Theobald
2011 Lecture Notes in Computer Science  
Experiments over a set of recursive queries and a very large knowledge base, consisting of 20 million RDF facts, as well as comparisons to disk-oriented reasoning engines, confirm the practical viability  ...  Deductive reasoning lies in the expressive intersection of Datalog and Description Logics.  ...  The Semantic Web has led to the development of several reasoning engines which support either classical Datalog-style (rule-based) reasoning, or RDF/S-and OWL-based reasoning capabilities.  ... 
doi:10.1007/978-3-642-24908-2_14 fatcat:4e4ggvijkzc7vfkred22z2srw4

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)  
However, reasoning approaches need to be scalable in order to enable reasoning over the entire Web of Data.  ...  methods and over the conducted experiments.  ...  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 "III: Small: TROn -Tractable Reasoning  ... 
doi:10.1017/s0269888918000255 fatcat:bergc5uphbceznigppektgvzrm

BigDataGrapes D4.2 - Methods and Tools for Distributed Inference

Milena Yankova, Boyan SImeonov, Atanas Kiryakov, Vladimir Alexiev
2018 Zenodo  
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 second challenge is how the actual inference over distributed sources can be performed and implemented.  ...  They implement backward-chaining based on the QSQ (querysubquery) algorithm for Datalog databases modified to support reasoning over OWL RL.  ... 
doi:10.5281/zenodo.1481809 fatcat:7jkignzjnfdmxomknr5vjrwhhm

DynamiTE: Parallel Materialization of Dynamic RDF Data [chapter]

Jacopo Urbani, Alessandro Margara, Ceriel Jacobs, Frank van Harmelen, Henri Bal
2013 Lecture Notes in Computer Science  
One of the main advantages of using semantically annotated data is that machines can reason on it, deriving implicit knowledge from explicit information.  ...  We have evaluated the performance using a prototype system called DynamiTE , which organizes the knowledge bases with a number of indices to facilitate the query process and exploits parallelism to improve  ...  To formalize our problem in Datalog, let P be a program consisting of the rules in Table 1 , and I a given database, which represents the initial RDF knowledge base expressed as a set of Datalog facts  ... 
doi:10.1007/978-3-642-41335-3_41 fatcat:ns2v6wqukbfcbbgsw36fl7ifpe

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  
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  ...  The columns are ordered lexicographically, enabling fast merge joins and duplicate elimination, as well as data compression schemes for low memory usage.  ...  On average, VLog uses only 40% of the memory required by RDFox, ostensibly due to its compressed data structures.  ... 
doi:10.1007/978-3-319-94205-6_44 fatcat:ceirdsuqkne2beituhy4eyyhq4

BigDataGrapes D4.2 - Methods and Tools for Distributed Inference

Milena Yankova, Boyan SImeonov, Atanas Kiryakov, Vladimir Alexiev
2019 Zenodo  
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 second challenge is how the actual inference over distributed sources can be performed and implemented.  ...  Main disadvantage of this scenario comes from the fact that the knowledge graph data in GraphDB can evolve and this requires proper synchronisation mechanisms between already materialised inference in  ... 
doi:10.5281/zenodo.2629568 fatcat:amfv6a5euncnndfhsbgubr4i6q

Automating Data Citation: The eagle-i Experience

Abdussalam Alawini, Leshang Chen, Susan B. Davidson, Natan Portilho Da Silva, Gianmaria Silvello
2017 2017 ACM/IEEE Joint Conference on Digital Libraries (JCDL)  
In this paper, we therefore propose to use (positive) Datalog [3] as the model and specification language for RDF citation views, and show that they can be easily implemented using SPARQL. 4 https://www.w3  ...  RDF data 5 .  ...  They define a formal language of change for RDFS knowledge bases, and develop a change detection and application algorithm based on this language of change.  ... 
doi:10.1109/jcdl.2017.7991571 pmid:29599662 pmcid:PMC5868434 dblp:conf/jcdl/AlawiniCDSS17 fatcat:pm5s6nfer5h5vnzpt22qf27hsy

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.  ...  To the best of our knowledge, this is the first work to exploit a column-based approach for Datalog inferencing, and it does indeed seem as if the research on large-scale inmemory Datalog computation has  ... 
arXiv:1511.08915v2 fatcat:fnoxuh73lfabng676hdhjvbfja

Database Foundations for Scalable RDF Processing [chapter]

Katja Hose, Ralf Schenkel, Martin Theobald, Gerhard Weikum
2011 Lecture Notes in Computer Science  
The third part of the lecture is thus intended to provide a close-up on current approaches and platforms to make reasoning (e.g., in the form of probabilistic inference) with uncertain RDF data scalable  ...  Moreover, for the last part of this chapter, we argue that extracting knowledge from the Web is an excellent showcase -and potentially one of the biggest challenges -for the scalable management of uncertain  ...  Besides classical logic programming frameworks based on Prolog and Datalog, these engines specifically focus on different ontological reasoning concepts based on the RDF/S standards and the DL (based on  ... 
doi:10.1007/978-3-642-23032-5_4 fatcat:5owq3argizaj3epzu4yhuuxc6i

BigDataGrapes D4.2 - Methods and Tools for Distributed Inference

Milena Yankova, Boyan SImeonov, Atanas Kiryakov, Vladimir Alexiev
2020 Zenodo  
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 second challenge is how the actual inference over distributed sources can be performed and implemented.  ...  They implement backward-chaining based on the QSQ (querysubquery) algorithm for Datalog databases modified to support reasoning over OWL RL.  ... 
doi:10.5281/zenodo.4546071 fatcat:qwkhk7crvzgwvfz3dxzaqmy46m

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  ...  In this work, we focus instead on backward-chaining, and we present a general hybrid algorithm to perform efficient backward-chaining reasoning on very large RDF data sets.  ...  To the best of our knowledge, there is not (yet) a proper benchmark for reasoning over large data sets that extensively uses all the new features introduced with the OWL RL language.  ... 
doi:10.3233/sw-130120 fatcat:2r4i2m7kqzb67niw7ep4d5l5o4

WaterFowl: A Compact, Self-indexed and Inference-Enabled Immutable RDF Store [chapter]

Olivier Curé, Guillaume Blin, Dominique Revuz, David Célestin Faye
2014 Lecture Notes in Computer Science  
In this paper we present WaterFowl, a novel approach for the storage of RDF triples that addresses scalability issues through compression.  ...  This approach implies to make a distinction between the terminological and the assertional components of the knowledge base early in the process of data preparation, i.e., preprocessing the data before  ...  When considered together, RDF data and its vocabulary represent a knowledge base which presents the main advantage of consistently managing the data and metadata within the same data model.  ... 
doi:10.1007/978-3-319-07443-6_21 fatcat:7pdrbaimtrbi3bng47fh23c4ce

Reasoning over RDF Knowledge Bases using Deep Learning [article]

Monireh Ebrahimi, Md Kamruzzaman Sarker, Federico Bianchi, Ning Xie, Derek Doran, Pascal Hitzler
2018 arXiv   pre-print
In this paper, we show that it is possible to train a Deep Learning system on RDF knowledge graphs, such that it is able to perform reasoning over new RDF knowledge graphs, with high precision and recall  ...  Reasoning, i.e., the drawing of logical inferences from knowledge expressed in such standards, is traditionally based on logical deductive methods and algorithms which can be proven to be sound and complete  ...  [44] perform knowledge graph reasoning using RDF(S) [49, 50] , based on knowledge graph embeddings.  ... 
arXiv:1811.04132v1 fatcat:e42txhb2qvdsvj4bzuegxaxzvu

Querying Semantic Knowledge Bases with SQL-on-Hadoop

Martin Przyjaciel-Zablocki, Alexander Schätzle, Georg Lausen
2017 Proceedings of the 4th Algorithms and Systems on MapReduce and Beyond - BeyondMR'17  
The constant growth of semantically-annotated data and an increasing interest in cross-domain knowledge bases raises the need for expressive query languages for RDF and novel approaches that enable their  ...  In this paper, we continue our work on TriAL-QL, an expressive (SQL-like) RDF query language based on the Triple Algebra with Recursion [31] .  ...  It supports SPARQL 1.1, OWL reasoning, and benefits from indexes and a two-level compression strategy optimized for RDF. As a last competitor we chose the graph database system Neo4j [33] .  ... 
doi:10.1145/3070607.3070610 dblp:conf/sigmod/Przyjaciel-Zablocki17 fatcat:wt42dwt6infpzn2ywq6n564vlu
« Previous Showing results 1 — 15 out of 113 results