Creating knowledge databases for storing and sharing people knowledge automatically using group decision making and fuzzy ontologies

[1]  Robert LIN,et al.  NOTE ON FUZZY SETS , 2014 .

[2]  Enrique Herrera-Viedma,et al.  A model to represent users trust in recommender systems using ontologies and fuzzy linguistic modeling , 2015, Inf. Sci..

[3]  Robert Arp,et al.  Building Ontologies with Basic Formal Ontology , 2015 .

[4]  Eric Gossett,et al.  Big Data: A Revolution That Will Transform How We Live, Work, and Think , 2015 .

[5]  Nathan Marz,et al.  Big Data: Principles and best practices of scalable realtime data systems , 2015 .

[6]  Sungyoung Lee,et al.  Mapping evolution of dynamic web ontologies , 2015, Inf. Sci..

[7]  Enrique Herrera-Viedma,et al.  Managing incomplete preference relations in decision making: A review and future trends , 2015, Inf. Sci..

[8]  Enrique Herrera-Viedma,et al.  Consistency-Driven Automatic Methodology to Set Interval Numerical Scales of 2-Tuple Linguistic Term Sets and Its Use in the Linguistic GDM With Preference Relation , 2015, IEEE Transactions on Cybernetics.

[9]  Jiujun Cheng,et al.  Automatic Composition of Semantic Web Services Based on Fuzzy Predicate Petri Nets , 2015, IEEE Transactions on Automation Science and Engineering.

[10]  Michel Dumontier,et al.  Pharmacogenomic knowledge representation, reasoning and genome-based clinical decision support based on OWL 2 DL ontologies , 2015, BMC Medical Informatics and Decision Making.

[11]  Yong-Gi Kim,et al.  Type-2 fuzzy ontology-based semantic knowledge for collision avoidance of autonomous underwater vehicles , 2015, Inf. Sci..

[12]  Torben Bach Pedersen,et al.  Using Semantic Web Technologies for Exploratory OLAP: A Survey , 2015, IEEE Transactions on Knowledge and Data Engineering.

[13]  X. Liu,et al.  Big data mining yields novel insights on cancer , 2015, Nature Genetics.

[14]  Enrique Herrera-Viedma,et al.  On multi-granular fuzzy linguistic modeling in group decision making problems: A systematic review and future trends , 2015, Knowl. Based Syst..

[15]  Pradeep Kumar Ray,et al.  Validating an ontology-based algorithm to identify patients with Type 2 Diabetes Mellitus in Electronic Health Records , 2014, Int. J. Medical Informatics.

[16]  Manuel P. Cuéllar,et al.  A fuzzy ontology for semantic modelling and recognition of human behaviour , 2014, Knowl. Based Syst..

[17]  Enrique Herrera-Viedma,et al.  A New Consensus Model for Group Decision Making Problems With Non-Homogeneous Experts , 2014, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[18]  Enrique Herrera-Viedma,et al.  A quality based recommender system to disseminate information in a university digital library , 2014, Inf. Sci..

[19]  Francisco Chiclana,et al.  A social network analysis trust-consensus based approach to group decision-making problems with interval-valued fuzzy reciprocal preference relations , 2014, Knowl. Based Syst..

[20]  Adrian H. Zai,et al.  Applying operations research to optimize a novel population management system for cancer screening. , 2014, Journal of the American Medical Informatics Association : JAMIA.

[21]  Enrique Herrera-Viedma,et al.  A new linguistic computational model based on discrete fuzzy numbers for computing with words , 2014, Inf. Sci..

[22]  Zongmin Ma,et al.  Fuzzy Knowledge Management for the Semantic Web , 2014, Studies in Fuzziness and Soft Computing.

[23]  Saint John Walker.  Big Data: A Revolution That Will Transform How We Live, Work, and Think , 2014 .

[24]  Li Yan,et al.  Fuzzy Ontology Knowledge Bases Storage in Fuzzy Databases , 2014 .

[25]  J. Humberto Pérez-Cruz,et al.  Evolving intelligent system for the modelling of nonlinear systems with dead-zone input , 2014, Appl. Soft Comput..

[26]  I-En Liao,et al.  Ontology-based library recommender system using MapReduce , 2013, Cluster Computing.

[27]  Yadira Espinal.  Viktor Mayer-Schonberger and Kenneth Cukier, Big Data: A Revolution That Will Transform How We Live, Work and Think , 2013 .

[28]  Ajay B. Satpute,et al.  Neural reactivation links unconscious thought to decision-making performance. , 2013, Social cognitive and affective neuroscience.

[29]  Witold Pedrycz,et al.  A method based on PSO and granular computing of linguistic information to solve group decision making problems defined in heterogeneous contexts , 2013, Eur. J. Oper. Res..

[30]  M. Hosli,et al.  Introduction: Decision-Making in the European Union before and after the Lisbon Treaty , 2013 .

[31]  E. Herrera-Viedma,et al.  A new consensus model for group decision making using fuzzy ontology , 2013, Soft Comput..

[32]  Umberto Straccia,et al.  Aggregation operators for fuzzy ontologies , 2013, Appl. Soft Comput..

[33]  James Nga-Kwok Liu,et al.  Application of decision-making techniques in supplier selection: A systematic review of literature , 2013, Expert Syst. Appl..

[34]  Aiping Liu,et al.  Corticomuscular Activity Modeling by Combining Partial Least Squares and Canonical Correlation Analysis , 2013, J. Appl. Math..

[35]  Witold Pedrycz,et al.  Granular Computing: Analysis and Design of Intelligent Systems , 2013 .

[36]  Zhuming Bi,et al.  Operations Research (OR) in Service Industries: A Comprehensive Review , 2013 .

[37]  Hua Wang,et al.  Multigranular Uncertain Linguistic Prioritized Aggregation Operators and Their Application to Multiple Criteria Group Decision Making , 2013, J. Appl. Math..

[38]  Jie Lu,et al.  Ontology-supported case-based reasoning approach for intelligent m-Government emergency response services , 2013, Decis. Support Syst..

[39]  Christoph Lange,et al.  Ontologies and languages for representing mathematical knowledge on the Semantic Web , 2013, Semantic Web.

[40]  Viktor Mayer-Schnberger,et al.  Big Data: A Revolution That Will Transform How We Live, Work, and Think , 2013 .

[41]  R. Aslin,et al.  Rational snacking: Young children’s decision-making on the marshmallow task is moderated by beliefs about environmental reliability , 2013, Cognition.

[42]  Enrique Herrera-Viedma,et al.  A linguistic consensus model for Web 2.0 communities , 2013, Appl. Soft Comput..

[43]  A. Warleigh-Lack,et al.  Decision-making in the European Union , 2013 .

[44]  Samuel Madden,et al.  From Databases to Big Data , 2012, IEEE Internet Comput..

[45]  Vincenzo Loia,et al.  Hierarchical web resources retrieval by exploiting Fuzzy Formal Concept Analysis , 2012, Inf. Process. Manag..

[46]  Rung Ching Chen,et al.  A recommendation system based on domain ontology and SWRL for anti-diabetic drugs selection , 2012, Expert Syst. Appl..

[47]  Matteo Gaeta,et al.  RSS-based e-learning recommendations exploiting fuzzy FCA for Knowledge Modeling , 2012, Appl. Soft Comput..

[48]  Enrique Herrera-Viedma,et al.  A Mobile Group Decision Making Model for Heterogeneous Information and Changeable Decision Contexts , 2011, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[49]  Ju Wang,et al.  Reasoning and change management in modular fuzzy ontologies , 2011, Expert Syst. Appl..

[50]  Mobyen Uddin Ahmed,et al.  Case-Based Reasoning Systems in the Health Sciences: A Survey of Recent Trends and Developments , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[51]  Fernando Ortega.  Managing vagueness in ontologies , 2011 .

[52]  David Sánchez,et al.  Ontology-based information content computation , 2011, Knowl. Based Syst..

[53]  Huajun Chen,et al.  The Semantic Web , 2011, Lecture Notes in Computer Science.

[54]  Stephen J. Andriole,et al.  Business impact of Web 2.0 technologies , 2010, Commun. ACM.

[55]  Enrique Herrera-Viedma,et al.  A Mobile Decision Support System for Dynamic Group Decision-Making Problems , 2010, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[56]  Zongmin Ma,et al.  Automatic Fuzzy Semantic Web Ontology Learning from Fuzzy Object-Oriented Database Model , 2010, DEXA.

[57]  Frank van Harmelen,et al.  A reasonable Semantic Web , 2010, Semantic Web.

[58]  Enrique Herrera-Viedma,et al.  Analyzing consensus approaches in fuzzy group decision making: advantages and drawbacks , 2010, Soft Comput..

[59]  Enrique Herrera-Viedma,et al.  Dealing with incomplete information in a fuzzy linguistic recommender system to disseminate information in university digital libraries , 2010, Knowl. Based Syst..

[60]  Francisco Herrera,et al.  Computing with words in decision making: foundations, trends and prospects , 2009, Fuzzy Optim. Decis. Mak..

[61]  Tim O'Reilly,et al.  What is Web 2.0 , 2009 .

[62]  Enrique Herrera-Viedma,et al.  A Consensus Model for Group Decision Making Problems with Unbalanced Fuzzy Linguistic Information , 2009, Int. J. Inf. Technol. Decis. Mak..

[63]  Francisco Herrera,et al.  Cardinal Consistency of Reciprocal Preference Relations: A Characterization of Multiplicative Transitivity , 2009, IEEE Transactions on Fuzzy Systems.

[64]  Jennifer Trant,et al.  Studying Social Tagging and Folksonomy: A Review and Framework , 2009, J. Digit. Inf..

[65]  Matthias Samwald,et al.  The bio-zen plus ontology , 2008, Appl. Ontology.

[66]  Umberto Straccia,et al.  Managing uncertainty and vagueness in description logics for the Semantic Web , 2008, J. Web Semant..

[67]  Umberto Straccia,et al.  fuzzyDL: An expressive fuzzy description logic reasoner , 2008, 2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence).

[68]  Silvia Calegari,et al.  Fuzzy Ontology, Fuzzy Description Logics and Fuzzy-OWL , 2007, WILF.

[69]  Thomas Gruber,et al.  Ontology of Folksonomy: A Mash-Up of Apples and Oranges , 2007, Int. J. Semantic Web Inf. Syst..

[70]  Diego Calvanese,et al.  The description logic handbook: theory , 2003 .

[71]  Diego Calvanese,et al.  The Description Logic Handbook: Theory, Implementation, and Applications , 2003, Description Logic Handbook.

[72]  Steffen Staab,et al.  Ontology Learning for the Semantic Web , 2002, IEEE Intell. Syst..

[73]  Francisco Herrera,et al.  A model based on linguistic 2-tuples for dealing with multigranular hierarchical linguistic contexts in multi-expert decision-making , 2001, IEEE Trans. Syst. Man Cybern. Part B.

[74]  Francisco Herrera,et al.  A 2-tuple fuzzy linguistic representation model for computing with words , 2000, IEEE Trans. Fuzzy Syst..

[75]  Francisco Herrera,et al.  A fusion approach for managing multi-granularity linguistic term sets in decision making , 2000, Fuzzy Sets Syst..

[76]  B. C. Vickery,et al.  Ontologies , 1997, J. Inf. Sci..

[77]  R. Yager.  Quantifier guided aggregation using OWA operators , 1996, Int. J. Intell. Syst..

[78]  Ronald R. Yager,et al.  An approach to ordinal decision making , 1995, Int. J. Approx. Reason..

[79]  Didier Dubois,et al.  Readings in Fuzzy Sets for Intelligent Systems , 1993 .

[80]  Thomas R. Gruber,et al.  A translation approach to portable ontology specifications , 1993 .

[81]  R. Yager.  Connectives and quantifiers in fuzzy sets , 1991 .

[82]  Ronald R. Yager,et al.  On ordered weighted averaging aggregation operators in multicriteria decisionmaking , 1988, IEEE Trans. Syst. Man Cybern..

[83]  B. C. Brookes,et al.  Information Sciences , 2020, Cognitive Skills You Need for the 21st Century.

[84]  M. Satterthwaite,et al.  Individual decisions and group decisions: The fundamental differences , 1978 .

[85]  Lotfi A. Zadeh,et al.  The concept of a linguistic variable and its application to approximate reasoning-III , 1975, Inf. Sci..

[86]  Lotfi A. Zadeh,et al.  The concept of a linguistic variable and its application to approximate reasoning - II , 1975, Inf. Sci..

[87]  L. A. ZADEH,et al.  The concept of a linguistic variable and its application to approximate reasoning - I , 1975, Inf. Sci..