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RDFPath: Path Query Processing on Large RDF Graphs with MapReduce [chapter]

Martin Przyjaciel-Zablocki, Alexander Schätzle, Thomas Hornung, Georg Lausen
2012 Lecture Notes in Computer Science  
Our evaluation on a real world data set shows the applicability of RDFPath for investigating typical graph properties like shortest paths.  ...  The MapReduce programming model has gained traction in different application areas in recent years, ranging from the analysis of log files to the computation of the RDFS closure.  ...  on large RDF graphs.  ... 
doi:10.1007/978-3-642-25953-1_5 fatcat:mipqj26aezfilgn2vizoxxvzui

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  
In this article, we propose a distributed technique to perform materialization under the RDFS and OWL ter Horst semantics using the MapReduce programming model.  ...  On a large scale, the resources of single machines are no longer sufficient and we are required to distribute the process to improve performance.  ...  RDFS reasoning with MapReduce The closure under the RDFS semantics [14] can be computed by applying all RDFS rules iteratively on the input until no new data is derived.  ... 
doi:10.1016/j.websem.2011.05.004 fatcat:7hifunbllrf25fastlqnkt6bvi

A Semantic-Based Approach for Managing Healthcare Big Data: A Survey

Rafat Hammad, Malek Barhoush, Bilal H. Abed-alguni, Saverio Maietta
2020 Journal of Healthcare Engineering  
In the recent few years, a large number of organizations and companies have shown enthusiasm for using semantic web technologies with healthcare big data to convert data into knowledge and intelligence  ...  Based on our literature review, we will discuss how different techniques, standards, and points of view created by the semantic web community can participate in addressing the challenges related to healthcare  ...  [86] presented a scalable management system for RDF data which is based on the Hadoop MapReduce framework. e proposed architecture is based on using a graph partitioning algorithm to store triples that  ... 
doi:10.1155/2020/8865808 pmid:33489061 pmcid:PMC7787845 fatcat:gorgipqn6famhkeffmqzr4tacq

A Fine Grain Sentiment Analysis with Semantics in Tweets

Cristobal Barba Gonzalez, José García-Nieto, Ismael Navas-Delgado, José Aldana-Montes
2016 International Journal of Interactive Multimedia and Artificial Intelligence  
Microblogging sites like Twitter have millions of active users (320 million active users on Twitter on the 30th September 2015) who share their opinions in real time, generating huge amounts of data.  ...  We offer a combination of Big Data tools (under the Apache Hadoop framework) and sentiment analysis using RDF graphs supporting the study of the tweet's lexicon.  ...  A domain ontology guides the analysis process, providing sentiment values as RDF graphs [23] .  ... 
doi:10.9781/ijimai.2016.363 fatcat:w6kehyzkevee7gvsuexwr7lu7i

Partout: A Distributed Engine for Efficient RDF Processing [article]

Luis Galárraga, Katja Hose, Ralf Schenkel
2012 arXiv   pre-print
We propose an effective approach for fragmenting RDF data sets based on a query log, allocating the fragments to nodes in a cluster, and finding the optimal configuration.  ...  The increasing interest in Semantic Web technologies has led not only to a rapid growth of semantic data on the Web but also to an increasing number of backend applications with already more than a trillion  ...  ., after having applied a graph-partitioning algorithm on the complete data set (RDF graph), triples at the borders of the obtained partitions are replicated.  ... 
arXiv:1212.5636v1 fatcat:feug4weeffdxrmwmnrqvep7awi

CACAO: Conditional Spread Activation for Keyword Factual Query Interpretation [chapter]

Edgard Marx, Gustavo Correa Publio, Thomas Riechert
2019 Lecture Notes in Computer Science  
It discloses an approach that incorporates keyword graph structure dependencies through a conditional spread activation.  ...  This work copes with the problem of entity retrieval over RDF knowledge graphs using keyword factual queries.  ...  This work presents CACAO, a novel approach for ER on large 3 and diverse RDF KGs. It relies on a novel spread activation (SA) method to improve information access.  ... 
doi:10.1007/978-3-030-33220-4_19 fatcat:j7hevue3jzeqdbg2nrfenk5upa

Conceptualization with Incremental Bron-Kerbosch Algorithm in Big Data Architecture

2016 Acta Polytechnica Hungarica  
The analysis of the clique detection algorithm in MapReduce architecture provides efficiency comparison for large scale contexts.  ...  The proposed method uses a concept generation module based on clique detection in the context graph.  ...  easier to port graph algorithms on top of the MapReduce platform.  ... 
doi:10.12700/aph.13.2.2016.2.8 fatcat:op44d4t6rvaj7o3isf7tb7waiu

Big Data Analysis [chapter]

John Domingue, Nelia Lasierra, Anna Fensel, Tim van Kasteren, Martin Strohbach, Andreas Thalhammer
2016 New Horizons for a Data-Driven Economy  
obtain permission from the license holder to duplicate, adapt, or reproduce the material.  ...  unless indicated otherwise in the credit line; if such material is not included in the work's Creative Commons license and the respective action is not permitted by statutory regulation, users will need to  ...  They show that this applies to a variety of learning algorithms (Chu et al. 2007 ). The implementations shown in the paper led to the first version of the MapReduce machine learning library Mahout.  ... 
doi:10.1007/978-3-319-21569-3_5 fatcat:tsgu6i62nrdr3gg7vfvpjzc7b4

TriAD

Sairam Gurajada, Stephan Seufert, Iris Miliaraki, Martin Theobald
2014 Proceedings of the 2014 ACM SIGMOD international conference on Management of data - SIGMOD '14  
Our engine, coined "TriAD", combines joinahead pruning via a novel form of RDF graph summarization with a locality-based, horizontal partitioning of RDF triples into a gridlike, distributed index structure  ...  We investigate a new approach to the design of distributed, sharednothing RDF engines.  ...  In order to create the summary graph, we first consider this set of RDF facts as one large graph GD (using an intermediate dictionary for mapping node and edge labels to integer ids) and apply a non-overlapping  ... 
doi:10.1145/2588555.2610511 dblp:conf/sigmod/GurajadaSMT14 fatcat:tejrebkzsnaa7nspnbmkmorqtm

Deep learning based searching approach for RDF graphs

Hatem Soliman, Tao Song
2020 PLoS ONE  
First, we preprocess the RDF graphs to convert them into N-Triples format.  ...  The attention mechanism enables the proposed approach to understand the semantic between RDF graphs.  ...  To the best of our knowledge, we are the first to apply deep representation to learn the RDF graph representation.  ... 
doi:10.1371/journal.pone.0230500 pmid:32203547 fatcat:bp4vgox6szegrku7wlzjzujc4q

Knowledge Discovery from Social Media using Big Data provided Sentiment Analysis (SoMABiT) [article]

Mahdi Bohlouli, Jens Dalter, Mareike Dornhöfer, Johannes Zenkert, Madjid Fathi
2020 arXiv   pre-print
To this aim, the use of efficient analytic algorithms ensures a better understanding of customer feedback and improves the next generation of products.  ...  The use of MapReduce and developing a distributed algorithm towards an integrated platform that can scale for any data volume and provide a social media-driven knowledge is the main novelty of the proposed  ...  It provides a machine learning library on top of Hadoop, with the goal to provide machine learning algorithms that are scalable for large amounts of data.  ... 
arXiv:2001.05996v1 fatcat:q6fbnvhndjct5md4egj7eznh3m

Searching and browsing Linked Data with SWSE: The Semantic Web Search Engine

Aidan Hogan, Andreas Harth, Jürgen Umbrich, Sheila Kinsella, Axel Polleres, Stefan Decker
2011 Journal of Web Semantics  
Throughout, we offer evaluation and complementary argumentation to support our design choices, and also offer discussion on future directions and open research questions.  ...  Later, we also provide candid discussion relating to the difficulties currently faced in bringing such a search engine into the mainstream, and lessons learnt from roughly six years working on the Semantic  ...  Acknowledgements We would like to thank the anonymous reviewers and the editors for their feedback which helped to improve this paper.  ... 
doi:10.1016/j.websem.2011.06.004 fatcat:lteloasxhvgbhp3256ehrv5wf4

Searching and Browsing Linked Data with SWSE: The Semantic Web Search Engine

Aidan Hogan, Andreas Harth, JJrgen Umbrich, Sheila Kinsella, Axel Polleres, Stefan Decker
2011 Social Science Research Network  
Throughout, we offer evaluation and complementary argumentation to support our design choices, and also offer discussion on future directions and open research questions.  ...  Later, we also provide candid discussion relating to the difficulties currently faced in bringing such a search engine into the mainstream, and lessons learnt from roughly six years working on the Semantic  ...  Acknowledgements We would like to thank the anonymous reviewers and the editors for their feedback which helped to improve this paper.  ... 
doi:10.2139/ssrn.3199532 fatcat:ob2ko5yfbzcqpg3fgbrysqstzi

Techniques, Tools and Applications of Graph Analytic

Faiza Ameer, Muhammad Kashif, Ramzan Talib, Muhammad Umer, Zahid Khan, Khawar Zulfiqar, Ahmad Riasat
2019 International Journal of Advanced Computer Science and Applications  
Major challenge is to develop efficient systems to store, process and analyze large graphs generated by these applications.  ...  Graphs have acute significance because of polytropic nature and have wide spread real world big data applications, e.g., search engines, social media, knowledge discovery, network systems, etc.  ...  MapReduce model did not turn out to be ideal for many different graph algorithms, e.g. parallel BFS.  ... 
doi:10.14569/ijacsa.2019.0100443 fatcat:o7gxpklkubfuvebhohnafr7yge

Random Forest Based Searching Approach for RDF

Hatem Soliman
2020 IEEE Access  
First, we preprocess the RDF to convert them into N-Triples format. Then, a feature vector is constructed for each RDF using the preprocessed RDF.  ...  After that, a random forest classifier is trained for the prediction of the fetching status of RDFs. The proposed approach is evaluated on an open-source DBpedia dataset.  ...  The RDF graph represents the RDF into a graph, whereas RDF/XML can encode and represent the RDF graph into XML.  ... 
doi:10.1109/access.2020.2980155 fatcat:uic52sr7m5fdbo2mr6duea7334
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