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Large Scale Fuzzy pD * Reasoning Using MapReduce [chapter]

Chang Liu, Guilin Qi, Haofen Wang, Yong Yu
2011 Lecture Notes in Computer Science  
The MapReduce framework has proved to be very efficient for data-intensive tasks. Earlier work has tried to use MapReduce for large scale reasoning for pD * semantics and has shown promising results.  ...  While most of the optimizations used by the existing MapReduce framework for pD * semantics are also applicable for fuzzy pD * semantics, unique challenges arise when we handle the fuzzy information.  ...  MapReduce Algorithm for pD * Reasoning MapReduce is a programming model introduced by Google for large scale data processing [1] .  ... 
doi:10.1007/978-3-642-25073-6_26 fatcat:f5zqayakbrgmtmrbbvixssb3se

Reasoning with Large Scale Ontologies in Fuzzy pD* Using MapReduce

Chang Liu, Guilin Qi, Haofen Wang, Yong Yu
2012 IEEE Computational Intelligence Magazine  
Conclusion In this paper, we proposed MapReduce algorithms to process forward inference over large scale data using fuzzy pD * semantics (i.e. an extension of pD * semantics with fuzzy vagueness).  ...  As far as we know, this is the first work that applies the MapReduce framework to tackle large scale reasoning in fuzzy OWL.  ...  This join can be simply calculated using a MapReduce program. 5) Handling Vague SameAs Closure However, not all sameAs triples are certain sameAs triples.  ... 
doi:10.1109/mci.2012.2188589 fatcat:swiitidb7nhp5jjiqlcyy3nv5q

Large-Scale Reasoning with OWL [article]

Michael Ruster
2016 arXiv   pre-print
This paper outlines common approaches for efficient reasoning on large-scale data consisting of billions (10^9) of triples.  ...  The WebPIE reasoner is discussed in detail as an example for forward chaining using MapReduce for materialisation.  ...  The development of OWL 2 RL was partly influenced by OWL pD* [26] . Thus, both are frequently used for large-scale reasoning [e.g. 4, 15] .  ... 
arXiv:1602.04473v1 fatcat:4b3gdsoct5ge3a5txqw2ah23cu

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 this large and uncoordinated environment, reasoning can be used to check the consistency of the data and of associated ontologies, or to infer logical consequences which, in turn, can be used to obtain  ...  This is particularly true for the so-called Web of Data, in which data is semantically enriched and interlinked using ontologies.  ...  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

An overview of recent distributed algorithms for learning fuzzy models in Big Data classification

Pietro Ducange, Michela Fazzolari, Francesco Marcelloni
2020 Journal of Big Data  
These algorithms have been generally implemented by using ad-hoc programming paradigms, such as MapReduce, on specific distributed computing frameworks, such as Apache Hadoop and Apache Spark.  ...  In particular, Value focuses on the useful knowledge that may be mined from data.  ...  Thus, in the last years practitioners and researchers have experimented new distributed frameworks, specifically developed for large-scale data storage and processing over a large number of computers,  ... 
doi:10.1186/s40537-020-00298-6 fatcat:vutg2g544rcbpfhthhleg5sffy

Multiple Relevant Feature Ensemble Selection Based on Multilayer Co-Evolutionary Consensus MapReduce

Weiping Ding, Chin-Teng Lin, Witold Pedrycz
2018 IEEE Transactions on Cybernetics  
We construct an Iavailable for all kinds of industrial applications, and big effective MCCM model to handle feature ensemble selection of large-scale datasets with multiple relevant feature sources, data  ...  These classification prediction for large-scale and complex brain data in useless features often diminish the learning process associterms of efficiency and feasibility. ated with classification algorithms  ...  As a matter of fact, the divide-and-conquer strategy has long been used in large-scale retrieval and learning, just like the framework of CC and MapReduce.  ... 
doi:10.1109/tcyb.2018.2859342 pmid:30130243 fatcat:lk7dgvlfhjcj3exex3ddlgss7q

A Distributed Weighted Possibilistic c-Means Algorithm for Clustering Incomplete Big Sensor Data

Qingchen Zhang, Zhikui Chen
2014 International Journal of Distributed Sensor Networks  
) based on MapReduce.  ...  Finally, to improve the cluster speed of WPCM, the cloud computing technology is used to optimize the WPCM algorithm by designing the distributed weighted possibilistic c-means clustering algorithm (DWPCM  ...  Another example is hierarchical clustering algorithm based on cloud computing, in which MapReduce is used to optimize the hierarchical clustering algorithm for processing large-scale data [24, 25] .  ... 
doi:10.1155/2014/430814 fatcat:cijdzrcyhzg4zfzeka4p4il3u4

OWL Reasoning Framework over Big Biological Knowledge Network

Huajun Chen, Xi Chen, Peiqin Gu, Zhaohui Wu, Tong Yu
2014 BioMed Research International  
The derived associations are quite useful for biologists to promote the development of novel drugs and TCM modernization.  ...  In this paper, we present a general OWL (web ontology language) reasoning framework to study the implicit relationships among biological entities.  ...  [44] developed the MapReduce algorithms for materializing RDFS inference results. Liu et al. [45] extended the method to handle fuzzy pD reasoning. Oren et al.  ... 
doi:10.1155/2014/272915 pmid:24877076 pmcid:PMC4022201 fatcat:qoa7rzhjevhyfc7trpmwi6424u

DISTRIBUTED INDEXING: PERFORMANCE ANALYSIS OF SOLR, TERRIER AND KATTA INFORMATION RETRIEVALS

Ali Y. Aldailamy, Nor Asila Wati Abdul Hamid, Mohammed Abdulkarem
2018 Malaysian Journal of Computer Science  
High performance indexing is performed nowadays over the use of MapReduce programming model.  ...  Extremely, large data from different aspects is gathered each day resulting in huge increase in the scale of the raw data available across the internet.  ...  Therefore, the project then prolonged for supporting the decentralized environment and enables large-scale parallelized indexing utilizing Hadoop MapReduce distribution system.  ... 
doi:10.22452/mjcs.sp2018no1.7 fatcat:hrgzzf6efbfkplgtrl63dzuyw4

Editorial

Srikanta Patnaik, Srikanta Patnaik
2018 Journal of Intelligent & Fuzzy Systems  
to BA scale-free model.  ...  factor analysis and validates the reasonability and accuracy of the formulas using 432 tests data.  ... 
doi:10.3233/jifs-169562 fatcat:2qknpgafxjdaza2ppepzpwxreu

Rule-based Reasoning on Massively Parallel Hardware

Martin Peters, Christopher Brink, Sabine Sachweh, Albert Zündorf
2013 International Semantic Web Conference  
We evaluate our approach by applying the ρdf, RDFS and pD* rule sets to different data sets and compare our results with other recent work.  ...  Furthermore we show how vector-based operations can be used to implement a performant match algorithm.  ...  Other papers propose similar approaches also based on MapReduce differing in the implemented semantics like OWL 2 EL [11] or Fuzzy pD [12] .  ... 
dblp:conf/semweb/PetersBSZ13 fatcat:spnkq7ifkfaodnxjwjepiez7jm

A Dynamic and Combined Phishing Detection Technique

2020 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
The addition of multi-agent system to CBR-PDS provides a different efficient method to analyze phishing attacks in a greater scale.  ...  In this paper [4],a "case based reasoning -phishing detection system"(CBR-PDS) has been introduced .This system is checked against simple URL characteristics and intra-URL relatedness features to predict  ... 
doi:10.35940/ijitee.e2819.039520 fatcat:jfc3x2lbmnezzmd3gc423njfga

Parallel Frequent Subtrees Mining Method by an Effective Edge Division Strategy

Jing Wang, Xiongfei Li
2022 Applied Sciences  
EDS divides the edges with different frequencies into different intervals reasonably, which directly affects the task amount in each computing node.  ...  MapReduce is an ideal software framework to support distributed computing on large data sets on clusters of computers [10, 11] .  ...  Let the parent of node pd i i be node pd j j , and then pd i = |i − j|, where node pd 0 0 is the root node. Figure 1 . 1 Figure 1. An example tree. Figure 2 . 2 Figure 2.  ... 
doi:10.3390/app12094778 fatcat:mbprlwoycnetldmxceykgz5qam

The use of mobile phones to monitor the status of patients with Parkinson's disease

Yulia A. Shichkina, Galina V. Kataeva, Yulia A. Irishina, Elizaveta S. Stanevich
2020 Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications  
An apparatus of fuzzy logic was used to send data to the server; neural networks are used to process the data in the task of classifying the state of patients.  ...  about neural networks and used databases, and a change in Architecture of the information system for monitoring the status in patients with PD.  ...  To date, a very large set of various variants of membership functions has been accumulated for a wide variety of fuzzy statements [17, 18, 19] .  ... 
doi:10.22667/jowua.2020.06.30.055 dblp:journals/jowua/ShichkinaKIS20 fatcat:zorzadko5vhv7dz3tz2zlutifq

Efficient storage, retrieval and analysis of poker hands: An adaptive data framework

Marcin Gorawski, Michal Lorek
2017 International Journal of Applied Mathematics and Computer Science  
We also describe in detail how predicate based expression trees are used to build effective file-level execution plans.  ...  Both index types operate independently of the Hive execution context and allow other big data computational frameworks such as MapReduce or Spark to benefit from the optimized data access path to the hand  ...  Hadoop uses parallelism to perform at a huge scale.  ... 
doi:10.1515/amcs-2017-0049 fatcat:4fvajh46drf3lj5j6mnep5trta
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