{'fraction_non_alphanumeric': 0.018604651162790697, 'fraction_numerical': 0.0, 'mean_word_length': 5.09433962264151, '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}}
Finding k-Dominant Skyline for Combined Dataset

The k-dominant skyline query which can return small result set in high dimensional space is very convenient for user to make decision. But all the existent algorithms are for single dataset, not suitable for two or more datasets being combined. To solve this problem, this paper proposed a new idea to get the new k-dominant skyline by computing the partial points of each dataset based on their existent k-dominant skylines. Furthermore, detailed theoretical analyses and extensive experiments demonstrate that the algorithms can effectively reduce redundant work, and keep the result correctly.