Extracting knowledge-rich contexts for terminography
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Ingrid Meyer✝
Abstract
Knowledge-rich contexts express conceptual information for a term. Terminographers need such contexts to construct definitions, and to acquire domain knowledge. This paper summarizes what we have learned about extracting knowledge-rich contexts semi-automatically. First, we define the concept of a knowledge-rich context, its major types and its components. Second, we describe a methodology for developing extraction tools that is based on lexical, grammatical and paralinguistic patterns. Third, we outline the most problematic research issues that must be addressed before semi-automatic knowledge extraction can become a fully mature field.
Abstract
Knowledge-rich contexts express conceptual information for a term. Terminographers need such contexts to construct definitions, and to acquire domain knowledge. This paper summarizes what we have learned about extracting knowledge-rich contexts semi-automatically. First, we define the concept of a knowledge-rich context, its major types and its components. Second, we describe a methodology for developing extraction tools that is based on lexical, grammatical and paralinguistic patterns. Third, we outline the most problematic research issues that must be addressed before semi-automatic knowledge extraction can become a fully mature field.
Kapitel in diesem Buch
- Prelim pages i
- Table of contents vi
- Introduction viii
- A graph-based approach to the automatic generation of multilingual keyword clusters 1
- The automatic construction of faceted terminological feedback for interactive document retrieval 29
- Automatic term detection 53
- Incremental extraction of domain-specific terms from online text resources 89
- Knowledge-based terminology management in medicine 111
- Searching for and identifying conceptual relationships via a corpus-based approach to a Terminological Knowledge Base (CTKB) 127
- Qualitative terminology extraction 149
- General considerations on bilingual terminology extraction 167
- Detection of synonymy links between terms 185
- Extracting useful terms from parenthetical expressions by combining simple rules and statistical measures 209
- Software tools to support the construction of bilingual terminology lexicons 225
- Determining semantic equivalence of terms in information retrieval 245
- Term extraction using a similarity-based approach 261
- Extracting knowledge-rich contexts for terminography 279
- Experimental evaluation of ranking and selection methods in term extraction 303
- Corpus-based extension of a terminological semantic lexicon 327
- Term extraction for automatic abstracting 353
- About the contributors 371
- Subject Index 377
Kapitel in diesem Buch
- Prelim pages i
- Table of contents vi
- Introduction viii
- A graph-based approach to the automatic generation of multilingual keyword clusters 1
- The automatic construction of faceted terminological feedback for interactive document retrieval 29
- Automatic term detection 53
- Incremental extraction of domain-specific terms from online text resources 89
- Knowledge-based terminology management in medicine 111
- Searching for and identifying conceptual relationships via a corpus-based approach to a Terminological Knowledge Base (CTKB) 127
- Qualitative terminology extraction 149
- General considerations on bilingual terminology extraction 167
- Detection of synonymy links between terms 185
- Extracting useful terms from parenthetical expressions by combining simple rules and statistical measures 209
- Software tools to support the construction of bilingual terminology lexicons 225
- Determining semantic equivalence of terms in information retrieval 245
- Term extraction using a similarity-based approach 261
- Extracting knowledge-rich contexts for terminography 279
- Experimental evaluation of ranking and selection methods in term extraction 303
- Corpus-based extension of a terminological semantic lexicon 327
- Term extraction for automatic abstracting 353
- About the contributors 371
- Subject Index 377
