Multilingual Ontologies-based Extraction for Cross-Language Hybrid and Semantic Search
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The growth of multilingual web content portends the need for cross-language information retrieval. As a solution to this problem, we utilize ML-OntoES(a MultiLingual Ontology-based Extraction System). ML-OntoES enables hybrid keyword and semantic search over domain-specific, semi-structured information. Key ideas of ML-OntoES include monolingual semantic indexing and query interpretation with extraction ontologies and 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 hybrid and semantic search.
Abstract
The growth of multilingual web content portends the need for cross-language information retrieval. As a solution to this problem, we utilize ML-OntoES(a MultiLingual Ontology-based Extraction System). ML-OntoES enables hybrid keyword and semantic search over domain-specific, semi-structured information. Key ideas of ML-OntoES include monolingual semantic indexing and query interpretation with extraction ontologies and 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 hybrid and semantic search.
참고문헌 (21)
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