Machine Learning of Ambiguous Sentences and Analysis of Relation between Ambiguous Sentences and Diagrams in Technical Manual for Tacit Knowledge Acquisition
Abstract
Many companies create manuals to inherit the technology. Manuals contain a lot of information, but few are focused on tacit knowledge. Against this background, this research has two purposes, targeting manuals. First, it is to judge ambiguous sentences for mining tacit knowledge. Second, it is to clarify relation between ambiguous sentences and diagrams for mining tacit knowledge. This study was conducted with maintenance of railway rolling stock as the subject. At first, to confirm the hypothesis that ambiguous sentences include tacit knowledge, we compared result of mining by human and by machine learning. We obtained the results that we can recognize the ambiguous sentences by machine learning with high accuracy. The most striking observation to emerge from this data analysis was that ambiguous sentences can identified not only by adjectives and adverbs but also nouns, post positional particle, or conjunctions. Secondly, since many diagrams are used in the manual, it is thought that there were clues to mining tacit knowledge in the diagrams. As a result, it was found that there is a correlation between ambiguous sentences and diagrams.
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