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Institutional Repository [SANDBOX]
Technical University of Crete
Technical University of Crete
EN
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| URI: | http://purl.tuc.gr/dl/dias/218602D8-36D9-49B1-AD72-F229295EDB93 | ||
| Year | 2014 | ||
| Type of Item | Conference Full Paper | ||
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| Bibliographic Citation | S. Georgiladakis, Ch. Unger, E. Iosif, S. Walter, Ph. Cimiano, E. Petrakis and A. Potamianos, "Fusion of knowledge-based and data-driven approaches to grammar induction," presented at 15th Annual Conference of the International Speech Communication Association, Singapore, 2014. | ||
| Appears in Collections |
Using different sources of information for grammar induction results in grammars that vary in coverage and precision. Fusing such grammars with a strategy that exploits their strengths while minimizing their weaknesses is expected to produce grammars with superior performance. We focus on the fusion of grammarsproduced using a knowledge-based approach using lexicalized ontologies and a data-driven approach using semantic similarity clustering. We propose various algorithms for finding the mapping between the (non-terminal) rules generated by each grammar induction algorithm, followed by rule fusion. Three fusion approaches are investigated: early, mid and late fusion. Results show that late fusion provides the best relative F-measure performance improvement by 20%.
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