Coordinate descent based ontology sparse vector computing strategy and its applications

In recent years, as a semantic analysis and computational tool, ontology has been widely applied in many engineering applications. Many cases suggests that it’s confronted with countless big data source with the complex data structures. In order to relieve the dilemma, the sparse learning algorithms are introduced into the ontology similarity measuring and ontology mapping. In this setting, it should be a high dimensional expression of each ontology vertex, and the ontology algorithm should extract key component information effectively. Under such background, we consider the ontology sparse vector learning algorithm and application in different engineering applications. In this article, by means of coordinate descent minimization tricks, we present the ontology sparse vector optimization strategy and discuss the different transformation in different settings. At last, the new ontology sparse vector learning proceeding is applied to four engineering applications respectively to get its efficiency verified.

[1]  Nicola J. Mulder,et al.  A-DaGO-Fun: an adaptable Gene Ontology semantic similarity-based functional analysis tool , 2016, Bioinform..

[2]  Wei Gao,et al.  Stability Analysis of Learning Algorithms for Ontology Similarity Computation , 2013 .

[3]  Alexia Auffèves,et al.  Contexts, Systems and Modalities: A New Ontology for Quantum Mechanics , 2014, 1409.2120.

[4]  Jeffrey A. Fessler,et al.  Edge-Preserving Image Denoising via Group Coordinate Descent on the GPU , 2015, IEEE Transactions on Image Processing.

[5]  Yavor Nenov,et al.  Datalog rewritability of Disjunctive Datalog programs and non-Horn ontologies , 2016, Artif. Intell..

[6]  Wei Gao,et al.  Strong and weak stability of bipartite ranking algorithms , 2013, Other Conferences.

[7]  Peter Richtárik,et al.  Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function , 2011, Mathematical Programming.

[8]  Wei Gao,et al.  Ontology optimization tactics via distance calculating , 2016 .

[9]  Marco Masseroli,et al.  Ontology-Based Prediction and Prioritization of Gene Functional Annotations , 2016, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[10]  Sergio L. Toral Marín,et al.  A methodology for structured ontology construction applied to intelligent transportation systems , 2016, Comput. Stand. Interfaces.

[11]  David C. Hoyle,et al.  Statistical mechanics of ontology based annotations , 2016, ArXiv.

[12]  Wei Gao,et al.  The fifth geometric-arithmetic index of bridge graph and carbon nanocones , 2017 .

[13]  P. C. Sherimon,et al.  OntoDiabetic: An Ontology-Based Clinical Decision Support System for Diabetic Patients , 2016 .

[14]  Wei Gao,et al.  Ontology algorithm using singular value decomposition and applied in multidisciplinary , 2016, Cluster Computing.

[15]  Tülay Adali,et al.  Unbiased Recursive Least-Squares Estimation Utilizing Dichotomous Coordinate-Descent Iterations , 2014, IEEE Transactions on Signal Processing.

[16]  Amir Beck,et al.  The 2-Coordinate Descent Method for Solving Double-Sided Simplex Constrained Minimization Problems , 2013, Journal of Optimization Theory and Applications.

[17]  Mario Cannataro,et al.  Extracting Cross-Ontology Weighted Association Rules from Gene Ontology Annotations , 2016, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[18]  Chris Tampère,et al.  An extended coordinate descent method for distributed anticipatory network traffic control , 2015 .

[19]  Nguyen Van Duc Long,et al.  Novel retrofit designs using a modified coordinate descent methodology for improving energy efficiency of natural gas liquid fractionation process , 2016 .

[20]  Pornpit Wongthongtham,et al.  Ontology‐based employer demand management , 2016, Softw. Pract. Exp..

[21]  Ghassan Beydoun,et al.  Computationally efficient ontology selection in software requirement planning , 2014, Information Systems Frontiers.

[22]  Ion Necoara,et al.  Efficient random coordinate descent algorithms for large-scale structured nonconvex optimization , 2013, Journal of Global Optimization.

[23]  L. Bayón,et al.  Cyclic coordinate descent in a class of bang-singular-bang problems , 2016, J. Comput. Appl. Math..

[24]  Tom Michoel,et al.  Natural coordinate descent algorithm for L1-penalised regression in generalised linear models , 2014, Comput. Stat. Data Anal..

[25]  Ion Necoara,et al.  Random Coordinate Descent Methods for $\ell_{0}$ Regularized Convex Optimization , 2014, IEEE Transactions on Automatic Control.

[26]  Ion Necoara,et al.  A random coordinate descent algorithm for optimization problems with composite objective function and linear coupled constraints , 2013, Comput. Optim. Appl..

[27]  Peter Richtárik,et al.  On optimal probabilities in stochastic coordinate descent methods , 2013, Optim. Lett..

[28]  Umberto Straccia,et al.  The fuzzy ontology reasoner fuzzyDL , 2016, Knowl. Based Syst..

[29]  Franjo Cecelja,et al.  Ontology evaluation for reuse in the domain of Process Systems Engineering , 2016, Comput. Chem. Eng..

[30]  Rabih A. Jabr,et al.  Sensitivity-Based Discrete Coordinate-Descent for Volt/VAr Control in Distribution Networks , 2016, IEEE Transactions on Power Systems.

[31]  Stan Matwin,et al.  simDEF: definition-based semantic similarity measure of gene ontology terms for functional similarity analysis of genes , 2015, Bioinform..

[32]  Wei Gao,et al.  Ontology Sparse Vector Learning Algorithm for Ontology Similarity Measuring and Ontology Mapping via ADAL Technology , 2015, Int. J. Bifurc. Chaos.

[33]  Asunción Gómez-Pérez,et al.  Scheduling ontology development projects , 2016, Data Knowl. Eng..

[34]  M. Gillespie,et al.  Guidelines for the functional annotation of microRNAs using the Gene Ontology , 2016, RNA.

[35]  Wei Gao,et al.  Gradient Learning Algorithms for Ontology Computing , 2014, Comput. Intell. Neurosci..

[36]  Alexandru Balog,et al.  An Ontology-Based E-Learning Framework for Healthcare Human Resource Management* , 2016 .

[37]  Bogdan Dumitrescu.  On the relation between the randomized extended Kaczmarz algorithm and coordinate descent , 2014 .

[38]  Muhammad Younus Javed,et al.  DSont: DSpace to ontology transformation , 2016, J. Inf. Sci..

[39]  Robert I. M. Young,et al.  Reference ontologies to support the development of global production network systems , 2016, Comput. Ind..

[40]  Wei Gao,et al.  Margin based ontology sparse vector learning algorithm and applied in biology science , 2016, Saudi journal of biological sciences.

[41]  Wei Gao,et al.  Ranking based ontology scheming using eigenpair computation , 2016, J. Intell. Fuzzy Syst..

[42]  H. Park,et al.  Robust Coordinate Descent Algorithm Robust Solution Path for High-dimensional Sparse Regression Modeling , 2016, Commun. Stat. Simul. Comput..

[43]  Peter Richtárik,et al.  Accelerated, Parallel, and Proximal Coordinate Descent , 2013, SIAM J. Optim..

[44]  David Hawking,et al.  Overview of the TREC 2003 Web Track , 2003, TREC.

[45]  Mehrnoush Shamsfard,et al.  Symbiosis of evolutionary and combinatorial ontology mapping approaches , 2016, Inf. Sci..

[46]  K. Premkumar,et al.  IDENTIFICATION OF NOVEL GENES RELATED TO DIABETIC RETINOPATHY USING PROTEIN–PROTEIN INTERACTION NETWORK AND GENE ONTOLOGIES , 2016 .