A Comparative Study of Correlation Measurements for Searching Similar Tags

In recent years, folksonomy becomes a hot topic in many research fields such as complex systems, information retrieval, and recommending systems. It is essential to study the semantic relationships among tags in folksonomy applications. The main contributions of this paper includes: (a) proposes a general framework for the analysis of the semantic relationships among tags based on their co-occurrence. (b)investigates eight correlation measurements from various fields; then appliying these measurements to searching similar tags for a given tag on datasets from del.icio.us. (c) conducts a comparative study on both accuracy and time performance of the eight measurements. From the comparison, a best overall correlation measurement is concluded for similar tags searching in the applications of folksonomy.