Usability of upper level ontologies: The case of ResearchCyc

Abstract Repositories of knowledge about the real world are intended to serve as surrogates for the meaning and context of terms and concepts. These are being developed at two levels: (1) individual domain ontologies that capture concepts about a particular application domain; and (2) upper level ontologies that contain massive amounts of knowledge about the real world and are domain independent. This paper analyzes ResearchCyc, a version of Cyc, that attempts to capture common sense knowledge of the real world. Experience in applying ResearchCyc to web query processing is reported and the insights acquired are used to generate suggestions for improving the usability of upper level ontologies.

[1]  Michael J. Witbrock,et al.  Automated Population of Cyc: Extracting Information about Named-entities from the Web , 2006, FLAIRS.

[2]  Vijayan Sugumaran,et al.  Improving web-query processing through semantic knowledge , 2008, Data Knowl. Eng..

[3]  Olivier Bodenreider,et al.  The Unified Medical Language System (UMLS): integrating biomedical terminology , 2004, Nucleic Acids Res..

[4]  Alan L. Rector,et al.  Web ontology segmentation: analysis, classification and use , 2006, WWW '06.

[5]  Leo Obrst,et al.  The 2006 Upper Ontology Summit Joint Communiqué , 2006, Appl. Ontology.

[6]  Marvin Minsky,et al.  A conversation with Marvin Minsky about agents , 1994, CACM.

[7]  James A. Hendler,et al.  The Semantic Web" in Scientific American , 2001 .

[8]  David Baxter,et al.  On the Application of the Cyc Ontology to Word Sense Disambiguation , 2006, FLAIRS.

[9]  Michael J. Witbrock,et al.  A Knowledge-Based Approach to Network Security: Applying Cyc in the Domain of Network Risk Assessment , 2005, AAAI.

[10]  Douglas B. Lenat,et al.  CYC: a large-scale investment in knowledge infrastructure , 1995, CACM.

[11]  Michael J. Witbrock,et al.  Autonomous Classification of Knowledge into an Ontology , 2007, FLAIRS.

[12]  Xiaoyong Du,et al.  Ontology Construction for Semantic Web: A Role-Based Collaborative Development Method , 2005, APWeb.

[13]  Michael J. Witbrock,et al.  Searching for Common Sense: Populating Cyc™ from the Web , 2005, AAAI.

[14]  Jordi Conesa,et al.  A Method for Pruning Ontologies in the Development of Conceptual Schemas of Information Systems , 2006, J. Data Semant..

[15]  Vijayan Sugumaran,et al.  The role of domain ontologies in database design: An ontology management and conceptual modeling environment , 2006, TODS.

[16]  Kevin Knight,et al.  Toward Distributed Use of Large-Scale Ontologies t , 1997 .

[17]  P. Cochat,et al.  Et al , 2008, Archives de pediatrie : organe officiel de la Societe francaise de pediatrie.

[18]  Sudha Ram,et al.  Semantic conflict resolution ontology (SCROL): an ontology for detecting and resolving data and schema-level semantic conflicts , 2004, IEEE Transactions on Knowledge and Data Engineering.

[19]  Natalya F. Noy,et al.  Semantic integration: a survey of ontology-based approaches , 2004, SGMD.

[20]  Raphael Volz,et al.  Pruning-based Identification of Domain Ontologies , 2003, J. Univers. Comput. Sci..

[21]  Yanchun Zhang,et al.  Web Technologies Research and Development - APWeb 2005, 7th Asia-Pacific Web Conference, Shanghai, China, March 29 - April 1, 2005, Proceedings , 2005, APWeb.

[22]  Alexander Egyed.  Automated abstraction of class diagrams , 2002, TSEM.

[23]  Reind P. van de Riet,et al.  WORDNET++: A lexicon for the COLOR-X-method , 2001, Data Knowl. Eng..

[24]  Peter Wagner,et al.  Inducing criteria for mass noun lexical mappings using the Cyc KB, and its extension to WordNet , 2003 .

[25]  David Baxter,et al.  On the Effective Use of Cyc in a Question Answering System , 2005 .

[26]  David W. Embley,et al.  Towards Semantic Understanding -- An Approach Based on Information Extraction Ontologies , 2004, ADC.