Deriving concept hierarchies from text
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
An Approach for Measuring Semantic Similarity between Words Using Multiple Information Sources
IEEE Transactions on Knowledge and Data Engineering
Streams, structures, spaces, scenarios, societies (5s): A formal model for digital libraries
ACM Transactions on Information Systems (TOIS)
Towards the self-annotating web
Proceedings of the 13th international conference on World Wide Web
Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
"What is a good digital library?" - A quality model for digital libraries
Information Processing and Management: an International Journal
The complex dynamics of collaborative tagging
Proceedings of the 16th international conference on World Wide Web
Optimizing web search using social annotations
Proceedings of the 16th international conference on World Wide Web
Evaluation of digital libraries
International Journal on Digital Libraries
Using web metrics to analyze digital libraries
Proceedings of the 8th ACM/IEEE-CS joint conference on Digital libraries
Can all tags be used for search?
Proceedings of the 17th ACM conference on Information and knowledge management
Information retrieval in folksonomies: search and ranking
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
The semantic GrowBag algorithm: automatically deriving categorization systems
ECDL'07 Proceedings of the 11th European conference on Research and Advanced Technology for Digital Libraries
Uncovering hidden qualities - benefits of quality measures for automatically generated metadata
ECDL'10 Proceedings of the 14th European conference on Research and advanced technology for digital libraries
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In digital libraries semantic techniques are often deployed to reduce the expensive manual overhead for indexing documents, maintaining metadata, or caching for future search. However, using such techniques may cause a decrease in a collection's quality due to their statistical nature. Since data quality is a major concern in digital libraries, it is important to be able to measure the (loss of) quality of metadata automatically generated by semantic techniques. In this paper we present a user study based on a typical semantic technique used for automatic metadata creation, namely taxonomies of author keywords and tag clouds. We observed experts assessing typical relations between keywords and documents over a small corpus in the field of chemistry. Based on the evaluation of this experiment, we focused on communalities between the experts' perception and thus draw a first roadmap on how to evaluate semantic techniques by proposing some preliminary metrics.