{'fraction_non_alphanumeric': 0.008588957055214725, 'fraction_numerical': 0.0, 'mean_word_length': 5.634146341463414, '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}}
Traffic forecasting of mobile communication in call center

Along with the development of service industry and rapid growth of call volume in call center, traffic forecasting of mobile communication has become to be an urgent and significant issue especially when people are more and more concerned about customer service online. Based on the previous forecasting methods and thinking, this paper uses exponential smoothing model to forecast long term volume prediction-month calls volume, and establish an integrated regression forecasting model which takes practical situation into consideration and Markov chains for daily volume prediction. The comparison between the actual volume and predicted values show us that these provided models are fairly effective and feasible for traffic forecasting in call center.