Tags Are Related: Measurement of Semantic Relatedness Based on Folksonomy Network

Rok, strany: 2011, 165 - 185

Folksonomy and tagging systems, which allow users to interactively annotate a pool of shared resources using descriptive tags, have enjoyed phenomenal success in recent years. The concepts are organized as a map in human mind, however, the tags in folksonomy, which reflect users' collaborative cognition on information, are isolated with current approach. What we do in this paper is to estimate the semantic relatedness among tags in folksonomy: whether tags are related from semantic view, rather than isolated? We introduce different algorithms to form networks of folksonomy, connecting tags by users collaborative tagging, or by resource context. Then we perform multiple measures of semantic relatedness on folksonomy networks to investigate semantic information within them. The result shows that the connections between tags have relatively strong semantic relatedness, and the relatedness decreases dramatically as the distance between tags increases. What we find in this paper could provide useful visions in designing future folksonomy-based systems, constructing semantic web in current state of the Internet, and developing natural language processing applications.

ISO 690:

Wu, C., Zhou, B. 2011. Tags Are Related: Measurement of Semantic Relatedness Based on Folksonomy Network. In Computing and Informatics, vol. 30, no.1, pp. 165-185. 1335-9150.

APA:

Wu, C., Zhou, B. (2011). Tags Are Related: Measurement of Semantic Relatedness Based on Folksonomy Network. Computing and Informatics, 30(1), 165-185. 1335-9150.