¹Air Force Engineering University Graduate School, Xi'an, Shaanxi, China.
²Air Missile Defense College of Air Force Engineering University, Xi'an, Shaanxi, China.

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Abstract—With the rapid development of Internet technology in recent years, the sources of information materials are becoming more and more abundant. How to dig out useful information data from the vast network space and deal with it efficiently has become an urgent problem for the current intelligence agencies to solve. Aiming at the efficiency and quality of information facing the current intelligence agencies. In this paper, the characteristics and application requirements of intelligence data in cyberspace are analyzed. A new improved algorithm is proposed that based on Apriori algorithm. By setting double thresholds, frequent itemsets and non-frequent itemsets are extracted, the number of non-frequent itemsets is reduced, and then confidence, threshold judgment and non-frequent itemsets are used. Mining positive and negative association rules. Similarly, the integration of large information data in cyberspace is realized. Through induction and filtering of the integrated information data, the association rules are excavated, and the effective information is found. Finally, the effect of "assistant decision-making" is achieved.

Index Terms—Aprior algorithm, double threshold, frequent itemsets, positive and negative association rules, auxiliary decision.

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Cite: Zhang Jie, Wang Gang, "Intelligence Data Mining Based on Improved Apriori Algorithm," Journal of Computers vol. 14, no. 1, pp. 52-62, 2019.