Sequential data based CBR technique for market opportunity discovery

It is an important task related to the survival and development of enterprises to discover opportunities in the increasingly complex market. In face of massive opportunity information, it is inevitable for enterprises to utilize IT to support opportunity discovery tasks, especially for start-up enterprises. Case-Based Reasoning (CBR) technique adopts the idea of analogical reasoning, which can help enterprises to discover new opportunities from past opportunity discovery cases. According to the dynamic characteristics of opportunity discovery, in this paper we study the CBR method of opportunity discovery based on sequential data. We first mine the typical opportunity discovery patterns in the case base, and then investigate the support information of each case to the typical patterns to implement the similarity retrieval of cases. Finally the effectiveness of the method is demonstrated by a calculation instance.

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