Scientific Ontology Construction Based on Interval Valued Fuzzy Theory Under Web 2.0

Constructi on of the unified and shared domain ontology is significant for effective knowledge management. For the acquisition and sharing of scientific research knowledge under Web2.0, a novel approach of building Interval Valued Fuzzy Ontology ( IVFO ) in scientific research domain is presented. Through interval valued fuzzy theory, the definition and constructing framework of IVFO is proposed. Then IVFO is applied to semi-automatic extraction of information retrieval research domain. The preliminary constructing of research domain ontology is an essential base for the knowledge management system of scientific research. It can be effective methods for enhancing the efficiency and productivity of researching.

[1]  Wang Chao Ontology-based knowledge management modeling of scientific research , 2007 .

[2]  Zuhair Bandar,et al.  Sentence similarity based on semantic nets and corpus statistics , 2006, IEEE Transactions on Knowledge and Data Engineering.

[3]  SongDawei,et al.  Toward a Fuzzy Domain Ontology Extraction Method for Adaptive e-Learning , 2009 .

[4]  Bo Jiang,et al.  Ontology-Based Information Extraction of Crop Diseases on Chinese Web Pages , 2013, J. Comput..

[5]  Lei Liu,et al.  Construction of concept granule based on rough set and representation of knowledge-based complex system , 2011, Knowl. Based Syst..

[6]  Yan Lin,et al.  Semantic Retrieval Based on SPARQL and Fuzzy Ontology for Electronic Commerce , 2010, 2010 International Conference of Information Science and Management Engineering.

[7]  Hani Hagras,et al.  A Type-2 FML-Based Fuzzy Ontology for Dietary Assessment , 2013, On the Power of Fuzzy Markup Language.

[8]  Eder Mateus Nunes Gonçalves Specifying Knowledge in Cognitive Multiagent Systems Using a Class of Hierarchical Petri Nets , 2012, J. Softw..

[9]  Umberto Straccia,et al.  Towards a Fuzzy Description Logic for the Semantic Web (Preliminary Report) , 2005, ESWC.

[10]  Hani Hagras,et al.  A Type-2 Fuzzy Ontology and Its Application to Personal Diabetic-Diet Recommendation , 2010, IEEE Transactions on Fuzzy Systems.

[11]  Siu Cheung Hui,et al.  Automatic fuzzy ontology generation for semantic Web , 2006, IEEE Transactions on Knowledge and Data Engineering.

[12]  Nicola Guarino,et al.  Ontologies and Knowledge Bases. Towards a Terminological Clarification , 1995 .

[13]  H. Lan,et al.  SWRL : A semantic Web rule language combining OWL and ruleML , 2004 .

[14]  Wen-Hui Chen,et al.  Intelligent ontological agent for diabetic food recommendation , 2008, 2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence).

[15]  Siu Cheung Hui,et al.  A citation-based document retrieval system for finding research expertise , 2007, Inf. Process. Manag..

[16]  Vinícius Ramos Toledo Ferraz,et al.  A fuzzy ontology-based semantic data integration system , 2010, 2010 IEEE International Conference on Information Reuse & Integration.

[17]  Chang-Shing Lee,et al.  Ontology-based fuzzy event extraction agent for Chinese e-news summarization , 2003, Expert Syst. Appl..

[18]  Jerry M. Mendel,et al.  Type-2 fuzzy sets made simple , 2002, IEEE Trans. Fuzzy Syst..

[19]  Luigi Pontieri,et al.  A prototypal environment for collaborative work within a research organization , 2003, 14th International Workshop on Database and Expert Systems Applications, 2003. Proceedings..

[20]  Guilherme Horta Travassos,et al.  Scientific research ontology to support systematic review in software engineering , 2007, Adv. Eng. Informatics.

[21]  Peter Mika,et al.  Ontologies are us: A unified model of social networks and semantics , 2005, J. Web Semant..

[22]  Sheng-Yuan Yang,et al.  Developing an ontology-supported information integration and recommendation system for scholars , 2010, Expert Syst. Appl..

[23]  Raymond Y. K. Lau,et al.  Toward a Fuzzy Domain Ontology Extraction Method for Adaptive e-Learning , 2009, IEEE Transactions on Knowledge and Data Engineering.

[24]  Chang-Shing Lee,et al.  A fuzzy ontology and its application to news summarization , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[25]  Zhang Zhixiong,et al.  Practice of Creating and Reasoning Science Ontology by Protégé , 2009 .

[26]  Clare R. Voss,et al.  Fuzzy ontologies for multilingual document exploitation , 1999, 18th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.99TH8397).

[27]  Gleb Beliakov Fuzzy Sets and Membership Functions Based on Probabilities , 1996, Inf. Sci..

[28]  M. Mukaidono,et al.  Realization of sound-scape agent by the fusion of conceptual fuzzy sets and ontology , 1999, FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315).