Abstract
The growth of multilingual web content and increasing internationalization portends the need for cross-language query processing. We offer ML-OntoES (a MultiLingual Ontology-based Extraction System) as a solution for narrow-domain/data-rich applications. Based on language-independent extraction ontologies (Embley et al., Conceptual modeling foundations for a web of knowledge. In: Embley D, Thalheim B (eds) Handbook of conceptual modeling: theory, practice, and research challenges. Springer, Heidelberg, Germany, pp 477–516, 2011a), ML-OntoES enables semantic search over domain-specific, semistructured information. Key ideas of ML-OntoES include: (1) monolingual semantic indexing and query interpretation with extraction ontologies and (2) conceptual-level cross-language translation. A prototype implementation, along with experimental work showing good extraction accuracy in multiple languages, demonstrates the viability of the ML-OntoES approach of using multilingual extraction ontologies for cross-language query processing.
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Notes
- 1.
See, for example, http://www.clef-initiative.eu.
- 2.
Similar to the linguistic grounding discussed in Buitelaar et al. (2009), but different in its details.
- 3.
By π and σ, we mean projection and selection, respectively.
- 4.
Our mapping typology here resonates with that of León-Araúz and Faber (this volume), though our lexical type inventory is not as finely articulated.
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Acknowledgments
We are grateful to Tae Woo Kim and Rebecca Brinck for annotating our Korean and French document sets. We are also grateful to the reviewers for their insightful feedback and challenging questions.
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Embley, D.W., Liddle, S.W., Lonsdale, D.W., Shin, BJ., Tijerino, Y. (2014). Multilingual Extraction Ontologies. In: Buitelaar, P., Cimiano, P. (eds) Towards the Multilingual Semantic Web. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43585-4_10
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