{'fraction_non_alphanumeric': 0.019853709508881923, 'fraction_numerical': 0.0, 'mean_word_length': 5.302631578947368, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Exploiting Tagging in Ontology-based e-Learning

The ontologies are used to state the meaning of the terms used in data produced, shared and consumed within the context of Semantic Web applications. The folksonomies instead are an emergent phenomenon of the Social Web and represent the result of free tagging of information and objects in a social environment. Both ontologies and folksonomies are considered useful mechanisms to manage the information and are pretty always exploited, independently, in several areas of interest in order to cope with different problems related to searching, filtering, categorization and organization of content within some applications for e-commerce, e-learning, e-science, etc. In our opinion the two mechanisms are not in opposition but could be synergically used. In this paper we propose an approach based on the convergence between ontologies and folksonomies in order to improve personalised e-learning processes.