Method and system for aligning ontologies using annotation exchange

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Jul 22, 2010 - 22, 2010 Sheet 7 0f 18. US 2010/0185700 A1 r 200. . 115 ... Step 4: Insert a reference inside the received ontology to link the modified ...
US 20100185700A1

(19) United States (12) Patent Application Publication (10) Pub. No.: US 2010/0185700 A1 (43) Pub. Date:

Bodain (54)

(76)

METHOD AND SYSTEM FOR ALIGNING ONTOLOGIES USING ANNOTATION EXCHANGE Inventor:

Jul. 22, 2010

Publication Classi?cation

(51)

Int. Cl. G06F 17/30

(2006.01)

Yan Bodain, Montreal (CA) (52)

Correspondence Address: Miltons IP/p.i.

us. c1. ............................... .. 707/803;707/E17.044

(57)

225 Metcalfe Street, Suite 700

ABSTRACT

Ottawa, ON K2P 1P9 (CA)

Ontology alignment is achieved using an exchange of anno tations between different actors (users, software agent, appli

(21)

Appl. No .:

12/678,603

cation, etc.) over the Internet in order to create aligned ontolo gies that can be used by search engines to locate web content

(22)

PCT Filed:

Sep. 17, 2008

(86)

PCT No.:

PC T/CA08/01 632

§ 371 (0X1)’ (2), (4) Date:

Mar. 17, 2010

in the Semantic Web. An annotation related to a source ontol

ogy is received from a different storage medium. The ontol ogy associated with that annotation is retrieved in order to make a local copy. The copied ontology is renamed before its content can be modi?ed through a user interface. Every ele

ment modi?ed inside the copied ontology is then automati cally tagged with information in that links the modi?ed ele

Related US. Application Data

ment to the corresponding element in the source ontology.

Alignment between the copied ontology and the source ontol ogy is thereby achieved.

(63) Continuation-in-part of application No. 11/898,814, ?led on Sep. 17, 2007, now abandoned.

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METHOD AND SYSTEM FOR ALIGNING ONTOLOGIES USING ANNOTATION EXCHANGE FIELD OF INVENTION

[0014] LI, W. S., CLIFTON, C. (1994). Semantic Integra tion in Heterogeneous Databases Using Neural NetWorks. In Proc. of the 20th Int. Conf. on Very Large Data Bases

(VLDB), pp. 1-12 [0015] LI, W. S., CLIFTON, C. (2000). SemInt: A Tool for

Identifying Attribute Correspondences in Heterogeneous [0001]

The present invention relates to computers, and

more particularly to the use of annotation exchanges to create

aligned ontologies that can be used by search engines to locate Web content in the Semantic Web. REFERENCES CITED

[0002]

BERLIN, J ., MOTRO, A. (2002). Database Schema

Matching Using Machine Learning With Feature Selection. In Proc. of the 14th Int. Conf. on Advanced Information

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[0003] BERLIN, J., MOTRO, A. (2001). Autoplex: Auto mated Discovery of Content forVirtual Databases. In Proc. of the Int. Conf. on Cooperative Information Systems

(CoopIS), pp.108-122 [0004]

BERNERS-LEE, T. (1998), What the Semantic

Web can represent. Parenthetical discussion to the Web Architecture at 50,000 feet and the Semantic Web road

map. [http://WWW.W3.org/DesignIssues/RDFnot.html] [0005] CASTANO, S., DE ANTONELLIS, V. (1999). A Schema Analysis and Reconciliation Tool Environment. In Proc. of the 1999 Int. Symposium on Database Engineer

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Databases Using Neural NetWork. In Data and Knowledge Engineering, Vol. 33, No. 1, pp. 49-84 [0016] MADHAVAN, J ., BERNSTEIN, P. A., RAHM, E. (2001). Generic schema matching using Cupid. In Proc. of the 27th International Conference on Very Large Data Bases, pp. 49-58

[0017] MELNIK, S., GARCIA-MOLINA, H., RAHM, E. (2002). Similarity Flooding: A Versatile Graph Matching Algorithm. In Proc. of the 18th Int. Conf. on Data Engi

neering (ICDE), San Jose, Calif., USA, pp. 117-128 [0018]

MILLER, R. J. et al. (2001). The Clio Project: Man

aging Heterogeneity. In ACM SIGMOD Record, Vol.30, No.1, pp. 78-83

[0019] MILO, T., ZOHAR, S. (1998). Using Schema Matching to Simplify Heterogeneous Data Translation. In Proc. of the 24 Int. Conf. on Very Large Data Bases

(VLDB), pp. 122-133

[0020] MITRA, P., WIEDERHOLD, G., JANNINK, J. (1999). Semi-automatic Integration of KnoWledge Sources. In Proc. of Fusion’99, Sunnyvale, Calif., USA. [0021] NOY, N. F., MUSEN, M. A. (2000). PROMPT: algorithm and tool for automated ontology merging and alignment. In Proc. of the Seventeenth National Confer ence on Arti?cial Intelligence and TWelfth Conference on

Innovative Applications of Arti?cial Intelligence (AAAI),

(1997). Experience With a combined approach to attribute matching across heterogeneous databases. In Proc. of the IFIP Working Conference on Data Semantics (DS-7), pp.

[0022] OWL (Web Ontology Language), http://WWW.W3.

429-45 1 .

[0023] PALOPOLI, L., TERRACINA, G., URSINO, D.

[0007] CRUZ, I. F., SUNNA, W., MAKAR, N., BATHALA, S. (2007). A visual tool for ontology align ment to enable geospatial interoperability. In Journal of

Visual Languages and Computing & Computing, No.18, pp. 230-254

[0008] DO, H., AND RAHM, E. (2002). Coma: A system for fexible combination of schema matching approaches. In Proceedings of the 28th Conf. on Very Large Databases

(VLDB). [0009]

DOAN, A., MADHAVAN, J ., DHAMANKAR, R.,

Austin, Tex., pp. 450-455

org/TR/oWl-features/ (2000). The System DIKE: toWards the semi-automatic synthesis of Cooperative Information Systems and Data Warehouse. In Proc. Int. Symposium onAdvances in Data bases and Information Systems, Prague, pp. 108-117

[0024] RDF (Resource Description Framework), http:// WWW.W3 .org/RDF [0025] RDFa syntax, http://WWW.W3.org/2006/07/SWD/

RDFa/syntax/ [0026] SEMANTIC WEB, http://WWW.W3.org/2001/sW/ SHVAIKO,

Ontologies on the Semantic Web. In The Int. Journal on

[0027] P., EUZENAT, J. (2005). A survey of schema-based matching approaches. In Journal on Data Semantics, Vol.4,

Very Large Data Bases (VLDB), Vol.12, No.4,303-319. [0010] DOAN, A. H., DOMINGOS, P., HALEVY, A. (2001). Reconciling Schemas of Disparate Data Sources:

[0028] STUMME, G., MAEDCHE, A. (2001). FCA Merge: Bottom-up merging of ontologies. In Proc. of the

DOMINGOS, P., HALEVY, A. (2003). Learning to Match

A Machine-Learning Approach. In Proc. of the ACM SIG MOD Conf. on Management of Data, pp. 509-520

[0011] GUARINO, N. (1998) Formal Ontology and Infor mation Systems. In N. Guarino, (Ed.) Formal Ontology in Information Systems. IOS Press, Amsterdam, Nether lands. pp. 3-15

[0012] KLEIN, M. (2001). Combining and Relating Ontologies: An Analysis of Problems and Solutions. In

Workshop on Ontologies and Information Sharing (IJCAI 2001), Seattle, USA, pp. 309-327 [0013] KOTIS, K., VOUROS, G. A., STERGIOU, K. (2006). ToWards automatic merging of domain ontologies: The HCONE-merge approach. In Elsevier’s Journal of Web Semantics (JWS), Vol. 4, No. 1, pp. 60-79

pp. 146-171

17th Int. Joint Conference Conf. on Arti?cial Intelligence

(IJCAI ’01), USA, pp. 225-230 [0029]

The content of each and every one of these refer

ences is incorporated herein by reference. BACKGROUND OF THE INVENTION

[0030] The Web has been organiZed using syntactic and structural methods. Consequently, most major applications such as search, personalization, advertisements, and e-com merce, utiliZe syntactic and structural methods and apparatus. Directory services, such as those offered by Yahoo!, offer a

limited form of semantics by organiZing content by category or subjects, but the use of context and domain semantics is

minimal. When semantics is applied, critical Work is done by

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