AgreementMaker: Efficient Matching for Large Real-World Schemas and Ontologies

AgreementMaker: Efficient Matching for Large Real-World Schemas and Ontologies
AgreementMaker: Efficient Matching for Large Real-World Schemas and Ontologies
Bibliographical Metadata
Subject:	Ontology Alignment
Year:	2009
Authors:	Isabel F. Cruz, Flavio Palandri Antonelli, Cosmin Stroe
Venue	VLDB
Content Metadata
Problem:	Link Discovery
Approach:	No data available now.
Implementation:	AgreementMaker
Evaluation:	Performance Evaluation

Abstract

We present the AgreementMaker system for matching real-world schemas and ontologies, which may consist of hundreds or even thousands of concepts. The end users of the system are sophisticated domain experts whose needs have driven the design and implementation of the system: they require a responsive, powerful, and extensible framework to perform, evaluate, and compare matching methods. The system comprises a wide range of matching methods addressing di�erent levels of granularity of the components being matched (conceptual vs. structural), the amount of user intervention that they require (manual vs. automatic), their usage (stand-alone vs. composed), and the types of components to consider (schema only or schema and instances). Performance measurements (recall, precision, and runtime) are supported by the system, along with the weighted combination of the results provided by those methods. The AgreementMaker has been used and tested in practical applications and in the Ontology Alignment Evaluation Initiative (OAEI) competition. We report here on some of its most advanced features, including its extensible architecture that facilitates the integration and performance tuning of a variety of matching methods, its capability to evaluate, compare, and combine matching results, and its user interface with a control panel that drives all the matching methods and evaluation strategies.

Conclusion

No data available now.

Future work

No data available now.

Approach

Positive Aspects: No data available now.

Negative Aspects: No data available now.

Limitations: No data available now.

Challenges: No data available now.

Proposes Algorithm: No data available now.

Methodology: No data available now.

Requirements: No data available now.

Limitations: No data available now.

Implementations

Download-page: https://github.com/agreementmaker/agreementmaker

Access API: No data available now.

Information Representation: No data available now.

Data Catalogue: -

Runs on OS: No data available now.

Vendor: No data available now.

Uses Framework: No data available now.

Has Documentation URL: No data available now.

Programming Language: Java

Version: 0.23

Platform: No data available now.

Toolbox: No data available now.

GUI: No

Research Problem

Subproblem of: No data available now.

RelatedProblem: No data available now.

Motivation: No data available now.

Evaluation

Experiment Setup: No data available now.

Evaluation Method : Compare the mappings found by the system between the two ontologies with a reference matching or “gold standard,” which is a set of correct and complete mappings as built by domain experts.

Hypothesis: No data available now.

Description: No data available now.

Dimensions: Accuracy

Benchmark used: No data available now.

Results: Experiments have shown that our quality measure is usually effective in defining weights for the LWC matcher.