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    • 44. 发明申请
    • METHOD AND SYSTEM FOR MINING CHURN FACTOR CAUSING USER CHURN FOR NETWORK APPLICATION
    • 用于启动网络应用的用户切换的方法和系统
    • US20160314484A1
    • 2016-10-27
    • US15200718
    • 2016-07-01
    • TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED
    • JIE DONGXIAO WANG
    • G06Q30/02G06F17/30
    • G06Q30/0204G06F16/24578G06F16/2465G06F16/285
    • A method for mining a churn factor causing user churn for a network application includes: calculating, according to a data universe of churned users, a proportion of a quantity of churned users under each user operation scenario where user churn occurs for a network application in a total quantity of the churned users, and determining multiple user operation scenarios corresponding to multiple proportions sequentially placed in foremost positions in a list of all calculated proportions of user operation scenarios ranked in a descending order; determining churn factors of the multiple user operation scenarios; determining, according to the proportions of the churned users under the multiple user operation scenarios in all the churned users, influence weight values of the churn factors; and determining, when the influence weight value of a churn factor is greater than or equal to the threshold, that the churn factor is a major churn factor.
    • 一种用于为网络应用程序引起用户流失的流失因子的挖掘方法包括:根据所流动的用户的数据范围,计算在用户操作场景下的用户流失的一部分, 并且确定多个用户操作场景对应的多个用户操作场景,该多个用户操作场景顺序地放置在以降序排列的用户操作场景的所有计算比例的列表中的最前面的位置; 确定多个用户操作场景的流失因子; 根据在所有搅动用户中的多个用户操作场景下的搅动用户的比例来确定影响流失因子的权重值; 并且当搅拌因子的影响重量值大于或等于阈值时,确定搅拌因子是主要搅拌因子。
    • 45. 发明申请
    • OPERATIONAL DATA RATIONALIZATION
    • 操作数据归一化
    • US20160196510A1
    • 2016-07-07
    • US14590261
    • 2015-01-06
    • INTERNATIONAL BUSINESS MACHINES CORPORATION
    • Ravi Kumar Reddy KanamatareddySiba P. Satapathy
    • G06Q10/06G06F17/30G06N5/02
    • G06Q10/063G06F16/2465
    • An approach is provided for rationalizing operational data. A current data profile of a current dataset utilized by a current data transaction is determined. Persisted knowledge of previous data transactions is determined to include a previous data profile of a previous dataset that matches the current data profile. If the persisted knowledge indicates that data size and shape corrections were applied to the previous dataset, filtering corrections of the current dataset based on the data size and shape corrections are determined, the persisted knowledge is rationalized based on the filtering corrections, and queries of the current transaction are modified based on the filtering corrections, or if the data size and shape corrections were not applied to the previous dataset, the persisted knowledge is rationalized based on the data profile match and the queries of the current transaction are modified based on the rationalized persisted knowledge.
    • 为操作数据的合理化提供了一种方法。 确定当前数据事务利用的当前数据集的当前数据简档。 确定先前数据事务的持久知识包括与当前数据配置文件匹配的先前数据集的先前数据配置文件。 如果持续的知识表明数据大小和形状校正被应用于先前的数据集,则确定基于数据大小和形状校正的当前数据集的校正,基于过滤校正对持久知识进行合理化,并且 基于过滤修正修改当前事务,或者如果数据大小和形状校正未应用于上一个数据集,则基于数据配置文件匹配对持久化知识进行合理化,并且基于合理化的当前事务的查询进行修改 坚持知识