Automating Mini-Ontology Generation from Canonical Tables

Automating Mini-Ontology Generation from Canonical Tables Stephen Lynn Department of Computer Science Master of Science In this thesis work we develop and test MOGO (a Mini-Ontology GeneratOr.) MOGO automates the generation of mini-ontologies from canonicalized tables of data. This will help anyone trying to organize large amounts of existing data into a more searchable and accessible form. By using a number of different heuristic rules for selecting, enhancing, and modifying ontology elements, MOGO allows users to automatically, semi-automatically, or manually generate conceptual mini-ontologies from canonicalized tables of data. Ideally, MOGO operates fully automatically while allowing users to intervene to direct and correct when necessary so that they can always satisfactorily complete the translation of canonicalized tables into miniontologies. Experimental results show that MOGO is able to automatically identify the concepts, relationships, and constraints that exist in arbitrary tables of values with a relatively high level of accuracy. This automation significantly reduces the work required to translate canonicalized tables into mini-ontologies.

[1]  David W. Embley,et al.  Conceptual-Model-Based Data Extraction from Multiple-Record Web Pages , 1999, Data Knowl. Eng..

[2]  Helmut Berger,et al.  Improving Domain Ontologies by Mining Semantics from Text , 2004, APCCM.

[3]  David W. Embley,et al.  An Approach to Computation Specification for an Entity-Relationship Query Language , 1987, ER.

[4]  David W. Embley,et al.  Relational database reverse engineering: a model-centric, transformational, interactive approach formalized in model theory , 1997, Database and Expert Systems Applications. 8th International Conference, DEXA '97. Proceedings.

[5]  Michael Kifer,et al.  Logical foundations of object-oriented and frame-based languages , 1995, JACM.

[6]  David W. Embley.  Programming with data frames for everyday data items , 1980, AFIPS '80.

[7]  Veda C. Storey,et al.  Reverse Engineering of Relational Databases: Extraction of an EER Model from a Relational Database , 1994, Data Knowl. Eng..

[8]  Paul Johannesson,et al.  A method for transforming relational schemas into conceptual schemas , 1989, Proceedings of 1994 IEEE 10th International Conference on Data Engineering.

[9]  Sidi Mohamed Benslimane,et al.  Acquiring owl ontologies from data-intensive web sites , 2006, ICWE '06.

[10]  Isabelle Comyn-Wattiau,et al.  Extracting generalization hierarchies from relational databases: A reverse engineering approach , 2007, Data Knowl. Eng..

[11]  Steffen Staab,et al.  Learning Concept Hierarchies from Text Corpora using Formal Concept Analysis , 2005, J. Artif. Intell. Res..

[12]  Rudolf Wille,et al.  Formal Concept Analysis as Mathematical Theory of Concepts and Concept Hierarchies , 2005, Formal Concept Analysis.

[13]  Reda Alhajj.  Extracting the extended entity-relationship model from a legacy relational database , 2003, Inf. Syst..

[14]  Christiane Fellbaum,et al.  Book Reviews: WordNet: An Electronic Lexical Database , 1999, CL.

[15]  Raymond Y. K. Lau,et al.  Mining Fuzzy Domain Ontology from Textual Databases , 2007, IEEE/WIC/ACM International Conference on Web Intelligence (WI'07).

[16]  Jacky Akoka,et al.  Reverse Engineering of Relational Database Physical Schema , 1996, ER.

[17]  Xinxin Wang,et al.  Tabular Abstraction, Editing, and Formatting , 1996 .

[18]  David W. Embley,et al.  Ontology generation from tables , 2003, Proceedings of the Fourth International Conference on Web Information Systems Engineering, 2003. WISE 2003..

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

[20]  Philipp Cimiano,et al.  Ontology learning and population from text - algorithms, evaluation and applications , 2006 .

[21]  David W. Embley,et al.  Object-oriented systems analysis - a model-driven approach , 1991, Yourdon Press Computing series.

[22]  C. Fellbaum.  An Electronic Lexical Database , 1998 .

[23]  York Sure-Vetter,et al.  Transforming arbitrary tables into logical form with TARTAR , 2007, Data Knowl. Eng..

[24]  William J. Premerlani,et al.  An approach for reverse engineering of relational databases , 1993, [1993] Proceedings Working Conference on Reverse Engineering.