{'fraction_non_alphanumeric': 0.016783216783216783, 'fraction_numerical': 0.0, 'mean_word_length': 4.728, '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}}
Interesting patterns using goal programming

Data mining leads to the discovery of large number of patterns, all of these patterns can not be of interest to user. So mining of interesting patterns from the set of mined patterns is an issue. According to the user's interest at particular time, set of interesting patterns can be mined; the interest of user can vary with the time. In this paper we proposed that using goal programming we can find the interesting patterns according to the user's requirement at particular time. In order to control the priority of interesting patterns we can attach the deviational variables. Set of interesting patterns can be mined according to the user's will at particular time.