Domain Concept Extraction Model Based on Folksonomy

Social annotation provides a convenient way to annotate shared content by allowing users to use any tag or keyword. While free folksonomy is widely used in social software implementations and especially in web services, it will play an important role in the semantic web services. However, such tags cannot offer the expressivity of ontologies, and the respective tags often lack context-independent and explicit semantic. In this paper, we describe a model to extract domain concept from social tags. The model mainly includes three modules: a) Detecting the noun terminology through mutual information, b) Applying semantic dictionary to disambiguate between tags, c) Filtering the domain concept via domain relevance and consensus. Finally, experimental results on real world data sets show that the model can effectively learn the domain concept from social tags, and the concept also has a high degree of generality and applicability.