{'fraction_non_alphanumeric': 0.017937219730941704, 'fraction_numerical': 0.0, 'mean_word_length': 5.767676767676767, '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}}
Information Extraction from Interviews to Obtain Tacit Knowledge: A Text Mining Application

One of the most challenging knowledge management tasks is to obtain, summarize, and present tacit knowledge. It is important to develop approaches for creating insightful summaries from the knowledge obtained. In this paper, we present different information extraction methods for summarizing interview transcripts. Manual, semi-automatic, and automatic text analysis are evaluated to transform tacit knowledge into explicit form and to substantially reduce the time required to perform this transformation. These approaches are described in the context of a real application.