研究了一種新的增量數據挖掘方法，通過對交易數據項集進行編碼后，把原始數據轉換成整數值隨機變量序列，得到該序列為馬爾可夫鏈，利用頻率代替轉移概率，建立了一個趨勢分析的模型。通過對超市銷售數據的分析表明，該方法具有簡單、實用的特點，得到了顧客對同一產品的不同品牌的選擇是沒有差別的。
關 鍵 詞 數據挖掘; 趨勢分析; 轉移概率矩陣; 增量

Abstract In the paper, a new increment method of data mining is presented. Based on encoding the transaction data item set, the original data is transformed into a integral variable series is proved to be a Markov chain in theory. And instead of transfer probability, frequency is used in transfer probability matrix. Then a module is built for trend analysis .The analysis for the sale data of supermarket indicates that the method is fine, and a nice result that customs choice is same to different bland of one product is received.
Key words data mining; trend analysis; transfer probability matrix; increment