{'fraction_non_alphanumeric': 0.018154311649016642, 'fraction_numerical': 0.0, 'mean_word_length': 5.755102040816326, '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}}
Study on optimization selection model of Web service discovery based on genetic algorithm

Traditional Web services, which are mainly technical specifications based on UDDI, provide service discovery by simple classification and key word matching, resulting in low precision ratio and recall ratio as well as low compatibility of service multiplexing and service composition. This paper, basing on Web service models and in combination with genetic algorithm, brings forward a multi-target optimization selection model based on similarity, QoS, matching degree, rating and feasibility of Web services, and provides an effective method for Web service discovery.