中文摘要：

Competitive intelligence(CI)is a key factor in helping business leaders gain and maintain competitive advantages.The emergence of big data and Web 2.0 has created new opportunities and more challenges for enterprises to effectively obtain CI.This paper attempts to explore a CI identification method based on strategic factors(SF).By filtering process before CI collection,the core CI,closely related to critical success factors and crisis inducement factors,are identified reliably and efficiently.Based on knowledge element model and multiattribute fusion method,emphasis is placed on the construction of a criterion function by which the SF thesaurus in achieving CI objectives is established.The advantages of this method lie not only in the capability of mining the core CI from massive data,but also in the foundation of efficient CI storage and analysis.This paper is of significance to make a thorough inquiry on CI obtaining and fusing methods of CI system in era of big data.Experiment results verified the feasibility and validity of this study.

英文摘要：

Competitive intelligence （CI） is a key factor in helping business leaders gain and maintain competitive advantages. The emergence of big data and Web 2.0 has created new opportunities and more challenges for enterprises to effectively obtain CI. This paper attempts to explore a CI identification method based on strategic factors （SF）. By filtering process before CI collection, the core CI, closely related to critical success factors and crisis inducement factors, are identified reliably and efficiently. Based on knowledge element model and multi- attribute fusion method, emphasis is placed on the construction of a criterion function by which the SF thesaurus in achieving CI objectives is established. The advantages of this method lie not only in the capability of mining the core CI from massive data, but also in the foundation of efficient CI storage and analysis. This paper is of significance to make a thorough inquiry on CI obtaining and fusing methods of CI system in era of big data. Experiment results verified the feasibility and validity of this study.