Snowball: extracting relations from large plain-text collections
DL '00 Proceedings of the fifth ACM conference on Digital libraries
Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Learning Domain Ontologies from Document Warehouses and Dedicated Web Sites
Computational Linguistics
Evaluating WordNet-based Measures of Lexical Semantic Relatedness
Computational Linguistics
Ontology-driven discourse analysis for information extraction
Data & Knowledge Engineering - Special issue: Natural language and database and information systems: NLDB 03
Extraction and use of linguistic patterns for modelling medical guidelines
Artificial Intelligence in Medicine
Pattern-based automatic taxonomy learning from the Web
AI Communications
ONTOGRABBING: Extracting Information from Texts Using Generative Ontologies
FQAS '09 Proceedings of the 8th International Conference on Flexible Query Answering Systems
Ontology-driven extraction of linguistic patterns for modelling clinical guidelines
AIME'05 Proceedings of the 10th conference on Artificial Intelligence in Medicine
ONTOGRABBING: Extracting Information from Texts Using Generative Ontologies
FQAS '09 Proceedings of the 8th International Conference on Flexible Query Answering Systems
Expert Systems with Applications: An International Journal
Proxemic conceptual network based on ontology enrichment for representing documents in IR
EKAW'12 Proceedings of the 18th international conference on Knowledge Engineering and Knowledge Management
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This paper describes an approach to indexing texts by their conceptual content using ontologies along with lexico-syntactic information and semantic role assignment provided by lexical resources. The conceptual content of meaningful chunks of text is transformed into conceptual feature structures and mapped into concepts in a generative ontology. Synonymous but linguistically quite distinct expressions are mapped to the same concept in the ontology. This allows us to perform a content-based search which will retrieve relevant documents independently of the linguistic form of the query as well as the documents.