{'fraction_non_alphanumeric': 0.020061728395061727, 'fraction_numerical': 0.0, 'mean_word_length': 5.240384615384615, '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}}
User-centric Trust-based Recommendation

Recommender Systems are widely used to achieve a pre-selection of items among a constantly growing variety of items. Last generation of recommender systems take into account trust between users. In this article, we propose several trust-based recommendation formulas that keep centered around the end-user and thus restrict information sharing to the user vicinity. Our proposed RS does not need any global knowledge: it limits data exchange to trusted friendship relations. A comparison of the proposed recommendation formulas with more classical ones is finally proposed, based on two kinds of simulation.