Ontology Learning for the Semantic Web
Ontology Learning for the Semantic Web
KAON - Towards a Large Scale Semantic Web
EC-WEB '02 Proceedings of the Third International Conference on E-Commerce and Web Technologies
ICADL '02 Proceedings of the 5th International Conference on Asian Digital Libraries: Digital Libraries: People, Knowledge, and Technology
Usage patterns of collaborative tagging systems
Journal of Information Science
Yago: a core of semantic knowledge
Proceedings of the 16th international conference on World Wide Web
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Deriving a large scale taxonomy from Wikipedia
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Learning concept hierarchies from text corpora using formal concept analysis
Journal of Artificial Intelligence Research
Stop thinking, start tagging: tag semantics emerge from collaborative verbosity
Proceedings of the 19th international conference on World wide web
Comparison of generality based algorithm variants for automatic taxonomy generation
IIT'09 Proceedings of the 6th international conference on Innovations in information technology
Predicting partial orders: ranking with abstention
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part I
Ontologies are us: a unified model of social networks and semantics
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
Information retrieval in folksonomies: search and ranking
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
Enhancing the navigability of social tagging systems with tag taxonomies
i-KNOW '11 Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies
Building directories for social tagging systems
Proceedings of the 20th ACM international conference on Information and knowledge management
Navigational efficiency of broad vs. narrow folksonomies
Proceedings of the 23rd ACM conference on Hypertext and social media
Proceedings of the 12th International Conference on Knowledge Management and Knowledge Technologies
How tagging pragmatics influence tag sense discovery in social annotation systems
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
Meaning as collective use: predicting semantic hashtag categories on twitter
Proceedings of the 22nd international conference on World Wide Web companion
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Recent research has demonstrated how the widespread adoption of collaborative tagging systems yields emergent semantics. In recent years, much has been learned about how to harvest the data produced by taggers for engineering light-weight ontologies. For example, existing measures of tag similarity and tag relatedness have proven crucial step stones for making latent semantic relations in tagging systems explicit. However, little progress has been made on other issues, such as understanding the different levels of tag generality (or tag abstractness), which is essential for, among others, identifying hierarchical relationships between concepts. In this paper we aim to address this gap. Starting from a review of linguistic definitions of word abstractness, we first use several large-scale ontologies and taxonomies as grounded measures of word generality, including Yago, Wordnet, DMOZ and WikiTaxonomy. Then, we introduce and apply several folksonomy-based methods to measure the level of generality of given tags. We evaluate these methods by comparing them with the grounded measures. Our results suggest that the generality of tags in social tagging systems can be approximated with simple measures. Our work has implications for a number of problems related to social tagging systems, including search, tag recommendation, and the acquisition of light-weight ontologies from tagging data.