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A Case learning model for ship collision avoidance based on automatic text analysis

The sailor operation experiences are quite important for ship collision avoidance, and some of which can be found in typical collision avoidance cases. In order to use these cases effectively, it is necessary to analysis these recorded cases and learn some knowledge from them, furthermore, provide effective support for automatic collision avoidance decision making system. A case learning model based on automatic text analysis is proposed in this paper. Some useful cases and knowledge can be created from text format cases and stored in computer by use this case learning model. Some main treatments and algorithms, such as automatic Chinese word segmentation, disambiguation and semantic analysis, are discussed in this paper.