Title :
The wordNet based semantic relationship between tags in folksonomies
Author :
Min, Qi Xin ; Uddin, Mohammed Nazim ; Jo, Geun-Sik
Author_Institution :
Intell. E-Commerce Syst. Lab., Inha Univ., Incheon, South Korea
Abstract :
Collaborative tagging is a popular method in social resource sharing system. The reason why collaborative tagging system becomes popular is users can freely tags on the resources, like Flickr1 and Delicious2. Any relationship between tags and resources are not made explicitly when tagging in folksonomy. Due to lack of semantic meaning, it is difficult for users to find related resources. Also, short of sufficient number of relevant tags increase the data sparsity which decreases the rate of information extraction against the user queries. Defining semantic relationship between tags, resources and users is an important research issue to retrieval of related information from folksonomies. In this paper, we propose a WordNet based method to find the semantic relationship between tags in folksonomy. Finally, the experiment results using Flickr data show our proposed method works well finding semantic relationship between tags in folksonomy.
Keywords :
Internet; classification; indexing; natural language processing; query processing; social networking (online); Delicious2; Flickr1; WordNet; collaborative tagging; data sparsity; folksonomies; information extraction; semantic relationship; social resource sharing system; user queries; Collaboration; Computer science; Content based retrieval; Data mining; Information retrieval; Intelligent systems; Internet; Resource management; Tagging; Taxonomy; WordNet; folksonomies; information retrieval; tag;
Conference_Titel :
Computer and Automation Engineering (ICCAE), 2010 The 2nd International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-5585-0
Electronic_ISBN :
978-1-4244-5586-7
DOI :
10.1109/ICCAE.2010.5451821
