{'fraction_non_alphanumeric': 0.010526315789473684, 'fraction_numerical': 0.0, 'mean_word_length': 5.898550724637682, '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}}
Intelligent Open Spaces: Using Neural Networks for Prediction of Requested Resources in Smart Spaces

This paper describes how open spaces, a smart spaces pervasive architecture, can be used to capture human behavior and accordingly provide intelligent allocation responses to user requests. Our results show that learning the collective resource allocations and navigational patterns of users inside a particular location generates better predictions than learning per user.