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中文摘要：
提出了一种高效挖掘数据的频繁项目集模式的算法FIA．该算法采用一种二进制符号来表示数据，在仅扫描数据库一次之后，建立起二进制向量与上三角频繁项集矩阵，根据两者来产生出频繁项集．从而有效地缩小了搜索空间，加快了处理速度．通过实验表明，FIA算法比Apriori算法更有效．
英文摘要：
The traditional algorithms for mining association frequent patterns generate conditional sub tables, which costs much runtime and memory space. To solve these problems, a new algorithm FIA （Frequent Itemset Algorithm） is proposed. The FIA algorithm adopts a binary of symbols to compress the store data. The algorithm using logic of symbols to express data in a database, which only after one scan, and establish a binary vector and upper triangular frequent matrix, according to the both to produce a set of frequently. Thereby effectively narrowing the search space, speed up the processing speed. Through analysis showed that, FIA algorithm more effective than Apriori algorithm.
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