Database watermarking technologies provide an effective solution to data security problems by embedding the watermark in the database to prove copyright or trace the source of data leakage.However,when the watermarked...Database watermarking technologies provide an effective solution to data security problems by embedding the watermark in the database to prove copyright or trace the source of data leakage.However,when the watermarked database is used for data mining model building,such as decision trees,it may cause a different mining result in comparison with the result from the original database caused by the distortion of watermark embedding.Traditional watermarking algorithms mainly consider the statistical distortion of data,such as the mean square error,but very few consider the effect of the watermark on database mining.Therefore,in this paper,a consistency preserving database watermarking algorithm is proposed for decision trees.First,label classification statistics and label state transfer methods are proposed to adjust the watermarked data so that the model structure of the watermarked decision tree is the same as that of the original decision tree.Then,the splitting values of the decision tree are adjusted according to the defined constraint equations.Finally,the adjusted database can obtain a decision tree consistent with the original decision tree.The experimental results demonstrated that the proposed algorithm does not corrupt the watermarks,and makes the watermarked decision tree consistent with the original decision tree with a small distortion.展开更多
微软的SQL Server2000是当今最流行的数据库管理软件之一,研究了在SQL Server 2000上数据挖掘实现方面的决策树算法。决策树算法通过构造精度高、小规模的决策树采掘训练集中的分类知识。SQL Server 2000/Analysis Service两层结构决策...微软的SQL Server2000是当今最流行的数据库管理软件之一,研究了在SQL Server 2000上数据挖掘实现方面的决策树算法。决策树算法通过构造精度高、小规模的决策树采掘训练集中的分类知识。SQL Server 2000/Analysis Service两层结构决策树,采用了以类记数表及深度优先策略生成,在建树算法和数据库间设立数据挖掘中间件。并讨论了通过使用像SQL Server 2000 Analysis Service这样的典型工具来如何实现数据挖掘模型的创建,且为商业组织的决定挖掘出必要的数据。展开更多
Data mining is a procedure of separating covered up,obscure,however possibly valuable data from gigantic data.Huge Data impactsly affects logical disclosures and worth creation.Data mining(DM)with Big Data has been br...Data mining is a procedure of separating covered up,obscure,however possibly valuable data from gigantic data.Huge Data impactsly affects logical disclosures and worth creation.Data mining(DM)with Big Data has been broadly utilized in the lifecycle of electronic items that range from the structure and generation stages to the administration organize.A far reaching examination of DM with Big Data and a survey of its application in the phases of its lifecycle won't just profit scientists to create solid research.As of late huge data have turned into a trendy expression,which constrained the analysts to extend the current data mining methods to adapt to the advanced idea of data and to grow new scientific procedures.In this paper,we build up an exact assessment technique dependent on the standard of Design of Experiment.We apply this technique to assess data mining instruments and AI calculations towards structure huge data examination for media transmission checking data.Two contextual investigations are directed to give bits of knowledge of relations between the necessities of data examination and the decision of an instrument or calculation with regards to data investigation work processes.展开更多
许多人在淘宝网上免费开设了店铺。店铺不仅需要新顾客的加入也需要老顾客的稳定。根据店铺的销售记录运用ID3决策树算法,得到决定顾客是否稳定的关键因素是评价。同时在SQL Server 2005的决策树算法下进行验证。这一研究可以帮助店铺...许多人在淘宝网上免费开设了店铺。店铺不仅需要新顾客的加入也需要老顾客的稳定。根据店铺的销售记录运用ID3决策树算法,得到决定顾客是否稳定的关键因素是评价。同时在SQL Server 2005的决策树算法下进行验证。这一研究可以帮助店铺开设人员进行科学管理,稳定网店的顾客群。展开更多
基金supported by the National Key Research and Development Program of China under Grant 2021YFB2700600the National Natural Science Foundation of China under Grant 62132013 and 61902292+1 种基金the Key Research and Development Programs of Shaanxi under Grants 2021ZDLGY06-03the Truth-Seeking Research Scholarship Fund of Xidian University。
文摘Database watermarking technologies provide an effective solution to data security problems by embedding the watermark in the database to prove copyright or trace the source of data leakage.However,when the watermarked database is used for data mining model building,such as decision trees,it may cause a different mining result in comparison with the result from the original database caused by the distortion of watermark embedding.Traditional watermarking algorithms mainly consider the statistical distortion of data,such as the mean square error,but very few consider the effect of the watermark on database mining.Therefore,in this paper,a consistency preserving database watermarking algorithm is proposed for decision trees.First,label classification statistics and label state transfer methods are proposed to adjust the watermarked data so that the model structure of the watermarked decision tree is the same as that of the original decision tree.Then,the splitting values of the decision tree are adjusted according to the defined constraint equations.Finally,the adjusted database can obtain a decision tree consistent with the original decision tree.The experimental results demonstrated that the proposed algorithm does not corrupt the watermarks,and makes the watermarked decision tree consistent with the original decision tree with a small distortion.
文摘微软的SQL Server2000是当今最流行的数据库管理软件之一,研究了在SQL Server 2000上数据挖掘实现方面的决策树算法。决策树算法通过构造精度高、小规模的决策树采掘训练集中的分类知识。SQL Server 2000/Analysis Service两层结构决策树,采用了以类记数表及深度优先策略生成,在建树算法和数据库间设立数据挖掘中间件。并讨论了通过使用像SQL Server 2000 Analysis Service这样的典型工具来如何实现数据挖掘模型的创建,且为商业组织的决定挖掘出必要的数据。
文摘Data mining is a procedure of separating covered up,obscure,however possibly valuable data from gigantic data.Huge Data impactsly affects logical disclosures and worth creation.Data mining(DM)with Big Data has been broadly utilized in the lifecycle of electronic items that range from the structure and generation stages to the administration organize.A far reaching examination of DM with Big Data and a survey of its application in the phases of its lifecycle won't just profit scientists to create solid research.As of late huge data have turned into a trendy expression,which constrained the analysts to extend the current data mining methods to adapt to the advanced idea of data and to grow new scientific procedures.In this paper,we build up an exact assessment technique dependent on the standard of Design of Experiment.We apply this technique to assess data mining instruments and AI calculations towards structure huge data examination for media transmission checking data.Two contextual investigations are directed to give bits of knowledge of relations between the necessities of data examination and the decision of an instrument or calculation with regards to data investigation work processes.
