Hints for Reviewing Empirical Work in Software Engineering
Empirical Software Engineering
Named entity extraction from noisy input: speech and OCR
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
Named Entity recognition without gazetteers
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
An Empirical Study about the Feelgood Factor in Pair Programming
METRICS '04 Proceedings of the Software Metrics, 10th International Symposium
Biography as events in time and space
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
User Evaluation Study of a Tagging Approach to Semantic Mapping
ESWC 2009 Heraklion Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications
ProcessTron: efficient semi-automated markup generation for scientific documents
Proceedings of the 10th annual joint conference on Digital libraries
ECDL'10 Proceedings of the 14th European conference on Research and advanced technology for digital libraries
Does automated white-box test generation really help software testers?
Proceedings of the 2013 International Symposium on Software Testing and Analysis
| Hi-index | 0.00 |
Digitized scientific documents should be marked up according to domain-specific XML schemas, to make maximum use of their content. Such markup allows for advanced, semantics-based access to the document collection. Many NLP applications have been developed to support automated annotation. But NLP results often are not accurate enough; and manual corrections are indispensable. We therefore have developed the GoldenGATE editor, a tool that integrates NLP applications and assistance features for manual XML editing. Plain XML editors do not feature such a tight integration: Users have to create the markup manually or move the documents back and forth between the editor and (mostly command line) NLP tools. This paper features the first empirical evaluation of how users benefit from such a tight integration when creating semantically rich digital libraries. We have conducted experiments with humans who had to perform markup tasks on a document collection from a generic domain. The results show clearly that markup editing assistance in tight combination with NLP functionality significantly reduces the user effort in annotating documents.