{'fraction_non_alphanumeric': 0.01020408163265306, 'fraction_numerical': 0.0, 'mean_word_length': 5.740458015267175, '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 Lexical Relations for the Reuse of Investigation Reports

In this paper, we propose a reuse approach for investigation reports. Air investigation reports are documents containing observations, findings and recommendations made by safety analysts about incidents involving an aircraft. Reusing these complex documents is a considerable task as substantial domain knowledge is required to exploit their content. We conducted experiments using statistical techniques to acquire salient lexical relations from a corpus of reports. Keyphrase extraction and cooccurrence analysis was performed to condensate the textual content of the reports. Text alignment was applied to find associations between the sections targeted as case problems and case solutions. We illustrate lexical relationships we obtained and we discuss how these can be exploited to reuse investigation reports.