Data Semantics Meets Knowledge Discovery in Databases

In the last 30 years two important fields were born and have developed rapidly: knowledge discovery and knowledge management based on semantics. In the present chapter we provide an overview of the interlinks between them, taking the perspective of the evolution of systems and platforms supporting knowledge discovery with the help of data semantics.

[1]  María S. Pérez-Hernández,et al.  Design and implementation of a data mining grid-aware architecture , 2007, Future Gener. Comput. Syst..

[2]  Ian J. Taylor,et al.  Web services composition for distributed data mining , 2005, 2005 International Conference on Parallel Processing Workshops (ICPPW'05).

[3]  Nada Lavrac,et al.  Orange4WS Environment for Service-Oriented Data Mining , 2012, Comput. J..

[4]  Le Gruenwald,et al.  A survey of data mining and knowledge discovery software tools , 1999, SKDD.

[5]  Abraham Bernstein,et al.  Towards Intelligent Assistance for a Data Mining Process , 2005 .

[6]  Li Yu-hua,et al.  Data mining ontology development for high user usability , 2008, Wuhan University Journal of Natural Sciences.

[7]  Gregory Piatetsky-Shapiro,et al.  Knowledge Discovery in Real Databases: A Report on the IJCAI-89 Workshop , 1991, AI Mag..

[8]  Alberto Anguita,et al.  OntoDataClean: Ontology-Based Integration and Preprocessing of Distributed Data , 2006, ISBMDA.

[9]  Claudia Diamantini,et al.  A virtual mart for knowledge discovery in databases , 2013, Inf. Syst. Frontiers.

[10]  Sunita Sarawagi,et al.  Data mining models as services on the internet , 2000, SKDD.

[11]  Graham J. Williams,et al.  PMML: An Open Standard for Sharing Models , 2009, R J..

[12]  Yongheng Wang,et al.  Outlier detection from massive short documents using domain ontology , 2010, 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems.

[13]  Anna Zamansky,et al.  A graded approach to database repair by context-aware distance semantics , 2016, Fuzzy Sets Syst..

[14]  Bruce G. Buchanan,et al.  Ontology-guided knowledge discovery in databases , 2001, K-CAP '01.

[15]  Nada Lavrac,et al.  Automating Knowledge Discovery Workflow Composition Through Ontology-Based Planning , 2011, IEEE Transactions on Automation Science and Engineering.

[16]  Padhraic Smyth,et al.  From Data Mining to Knowledge Discovery: An Overview , 1996, Advances in Knowledge Discovery and Data Mining.

[17]  Alex Alves Freitas,et al.  An empirical evaluation of hierarchical feature selection methods for classification in bioinformatics datasets with gene ontology-based features , 2018, Artificial Intelligence Review.

[18]  Mario Cannataro,et al.  A Data Mining Ontology for Grid Programming , 2003 .

[19]  Liang Zhu,et al.  SEM-PPA: A semantical pattern and preference-aware service mining method for personalized point of interest recommendation , 2017, J. Netw. Comput. Appl..

[20]  Nada Lavrac,et al.  ClowdFlows: Online workflows for distributed big data mining , 2017, Future Gener. Comput. Syst..

[21]  Katharina Morik,et al.  The MiningMart Approach to Knowledge Discovery in Databases , 2004 .

[22]  Saso Dzeroski,et al.  Towards a General Framework for Data Mining , 2006, KDID.

[23]  Xiaodong Zhu,et al.  Construction and management of automatical reasoning supported data mining metadata , 2011, 2011 International Conference on Business Management and Electronic Information.

[24]  Saso Dzeroski,et al.  Ontology of core data mining entities , 2014, Data Mining and Knowledge Discovery.

[25]  Anthony Rowe,et al.  The Design of Discovery Net: Towards Open Grid Services for Knowledge Discovery , 2003, Int. J. High Perform. Comput. Appl..

[26]  Yike Guo,et al.  An Architecture for Distributed Enterprise Data Mining , 1999, HPCN Europe.

[27]  Robert L. Grossman,et al.  The management and mining of multiple predictive models using the predictive modeling markup language , 1999, Inf. Softw. Technol..

[28]  Chengqi Zhang,et al.  Flexible Frameworks for Actionable Knowledge Discovery , 2010, IEEE Transactions on Knowledge and Data Engineering.

[29]  David Sánchez,et al.  An automatic approach for ontology-based feature extraction from heterogeneous textualresources , 2013, Eng. Appl. Artif. Intell..

[30]  Rüdiger Wirth,et al.  Towards Process-Oriented Tool Support for Knowledge Discovery in Databases , 1997, PKDD.

[31]  Franco Turini,et al.  KDDML: A middleware language and system for knowledge discovery in databases , 2006, Data Knowl. Eng..

[32]  Chieh-Yuan Tsai,et al.  A dynamic Web service based data mining process system , 2005, The Fifth International Conference on Computer and Information Technology (CIT'05).

[33]  Heiko Paulheim,et al.  Semantic Web in data mining and knowledge discovery: A comprehensive survey , 2016, J. Web Semant..

[34]  Abraham Bernstein,et al.  A survey of intelligent assistants for data analysis , 2013, CSUR.

[35]  Teodor-Florin Fortis,et al.  Webservices oriented data mining in knowledge architecture , 2009, Future Gener. Comput. Syst..

[36]  Pedram Sadeghian,et al.  An extensible service oriented distributed data mining framework , 2004, 2004 International Conference on Machine Learning and Applications, 2004. Proceedings..

[37]  Kweku-Muata Osei-Bryson,et al.  Ontology-based data mining model management for self-service knowledge discovery , 2017, Inf. Syst. Frontiers.

[38]  Robert L. Grossman,et al.  Deploying Analytics with the Portable Format for Analytics (PFA) , 2016, KDD.

[39]  Jiming Liu,et al.  Service-Oriented Distributed Data Mining , 2006, IEEE Internet Computing.

[40]  Heiner Stuckenschmidt,et al.  A probabilistic ontological framework for the recognition of multilevel human activities , 2013, UbiComp.

[41]  Ingo Mierswa,et al.  YALE: Yet Another Learning Environment , 2003 .

[42]  Abraham Bernstein,et al.  Towards cooperative planning of data mining workflows , 2009 .

[43]  Laurent Brisson,et al.  How to Semantically Enhance a Data Mining Process? , 2008, ICEIS.

[44]  Heiko Paulheim Exploiting Linked Open Data as Background Knowledge in Data Mining , 2013, DMoLD.

[45]  Ramesh Subramonian,et al.  Facilitating data mining on a net-work of workstations , 2000 .

[46]  Robert Bergevin,et al.  Semantic human activity recognition: A literature review , 2015, Pattern Recognit..

[47]  อนิรุธ สืบสิงห์,et al.  Data Mining Practical Machine Learning Tools and Techniques , 2014 .

[48]  Abraham Bernstein,et al.  The NExT System: Towards True Dynamic Adaptations of Semantic Web Service Compositions , 2007, ESWC.

[49]  Maurizio Panti,et al.  Una piattaforma per servizi di KDD , 2003, SEBD.

[50]  Xiaodong Zhu,et al.  An Extended Predictive Model Markup Language for Data Mining , 2010, WAIM.

[51]  Jiawei Han,et al.  Mining Multiple-Level Association Rules in Large Databases , 1999, IEEE Trans. Knowl. Data Eng..

[52]  Sushmita Mitra,et al.  Fuzzy clustering with biological knowledge for gene selection , 2014, Appl. Soft Comput..

[53]  Hans-Jürgen Appelrath,et al.  Context-aware replacement operations for data cleaning , 2011, SAC '11.

[54]  Wagner Meira,et al.  Anteater: A Service-Oriented Architecture for High-Performance Data Mining , 2006, IEEE Internet Computing.

[55]  Ian J. Taylor,et al.  Triana: a graphical Web service composition and execution toolkit , 2004, Proceedings. IEEE International Conference on Web Services, 2004..

[56]  Heiko Paulheim,et al.  Mining the Web of Linked Data with RapidMiner , 2015, J. Web Semant..

[57]  Jan Rauch,et al.  Roles of Medical Ontology in Association Mining CRISP-DM Cycle , 2004 .

[58]  Ian H. Witten,et al.  Data mining: practical machine learning tools and techniques, 3rd Edition , 1999 .

[59]  Domenico Talia The Open Grid Services Architecture: Where the Grid Meets the Web , 2002, IEEE Internet Comput..

[60]  Joydeep Ghosh,et al.  Evaluating the novelty of text-mined rules using lexical knowledge , 2001, KDD '01.

[61]  Maozhen Li,et al.  PaDDMAS: parallel and distributed data mining application suite , 2000, Proceedings 14th International Parallel and Distributed Processing Symposium. IPDPS 2000.

[62]  Ramakrishnan Srikant,et al.  Mining generalized association rules , 1995, Future Gener. Comput. Syst..