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小小惡鐵蟲(chóng) (初入文壇)
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[求助]
摘要漢譯英(計(jì)算機(jī)數(shù)據(jù)挖掘方面)
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為了應(yīng)對(duì)實(shí)際應(yīng)用中經(jīng)常遇到的頻繁更新的數(shù)據(jù),一種與時(shí)機(jī)判定相結(jié)合的關(guān)聯(lián)規(guī)則增量更新算法開(kāi)始被人們廣泛研究。丁虎在基于數(shù)據(jù)倉(cāng)庫(kù)的關(guān)聯(lián)規(guī)則抽樣算法中給出了一種基于完全頻繁項(xiàng)集的關(guān)聯(lián)規(guī)則差異度判定方法,它能夠充分表達(dá)數(shù)據(jù)集更新前后關(guān)聯(lián)規(guī)則的變化,減少關(guān)聯(lián)規(guī)則更新的次數(shù),因此得到比較廣泛的應(yīng)用,然而這種算法在計(jì)算新增數(shù)據(jù)頻繁項(xiàng)集時(shí)不夠準(zhǔn)確,本文將提出一種DFUP算法,該算法通過(guò)引入一個(gè)動(dòng)態(tài)數(shù)據(jù)庫(kù)來(lái)解決上述算法的不足。 關(guān)鍵字:關(guān)聯(lián)規(guī)則;增量更新;時(shí)機(jī)判定;關(guān)聯(lián)規(guī)則差異度 |
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In order to deal with the frequently updating of data in practice, association rules incremental updating algorithm combining with time judgment begun to be widely studied. DingHu gave an association rule difference degree judgment method based on the completely frequent itemsets. This method can fully express the changes of association rules before and after the dataset updating, and reduce the times of the updating of association rules, therefore, this method was widely used. However, this method is not very accurate when calculating the new frequent itemsets. DFUP algorithm is proposed in this paper, and this algorithm solves the problem of the above algorithm by introducing a dynamic database. Keywords: association rule, incremental updating, time judgment, association rule difference degree |
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