研究了一種新的增量數(shù)據(jù)挖掘方法，通過(guò)對(duì)交易數(shù)據(jù)項(xiàng)集進(jìn)行編碼后，把原始數(shù)據(jù)轉(zhuǎn)換成整數(shù)值隨機(jī)變量序列，得到該序列為馬爾可夫鏈，利用頻率代替轉(zhuǎn)移概率，建立了一個(gè)趨勢(shì)分析的模型。通過(guò)對(duì)超市銷(xiāo)售數(shù)據(jù)的分析表明，該方法具有簡(jiǎn)單、實(shí)用的特點(diǎn)，得到了顧客對(duì)同一產(chǎn)品的不同品牌的選擇是沒(méi)有差別的。
關(guān) 鍵 詞 數(shù)據(jù)挖掘; 趨勢(shì)分析; 轉(zhuǎn)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