{'fraction_non_alphanumeric': 0.016016016016016016, 'fraction_numerical': 0.0, 'mean_word_length': 5.0606060606060606, '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}}
Flexible Dynamic Recommender System

A Recommender System now becoming decision maker for the people who lack sufficient personal experience to evaluate the items that are on website. It provides recommendation for specific items such as books, news, tourism services etc. Personalization is common term for improving online services and attract more users. The previous recommender system like Amazon, Suggest, e-bay provide suggestion for specific items but drawback that service provider can see the ratings of users. It may happen that owner can give more ratings for particular item and can increase product popularity. This results in misguiding to user and privacy is violated. In our flexible recommender system users give ratings for some product in encrypted format, so service provider does not able to decrypt it. In this recommender system users decision time is saved, because time plays vital role in recommender system. During less amount of time user should get more rated products.