WO2012113279A1 - 要因失分的数据处理方法及设备 - Google Patents

要因失分的数据处理方法及设备 Download PDF

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Publication number
WO2012113279A1
WO2012113279A1 PCT/CN2012/070801 CN2012070801W WO2012113279A1 WO 2012113279 A1 WO2012113279 A1 WO 2012113279A1 CN 2012070801 W CN2012070801 W CN 2012070801W WO 2012113279 A1 WO2012113279 A1 WO 2012113279A1
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Prior art keywords
score
kpi
characterization
contribution
factor
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French (fr)
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徐红艳
曹艳霞
康绍莉
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Datang Mobile Communications Equipment Co Ltd
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Datang Mobile Communications Equipment Co Ltd
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Priority to EP12749322.9A priority Critical patent/EP2680633A4/en
Priority to US13/984,997 priority patent/US20130316701A1/en
Priority to KR1020137014668A priority patent/KR101663278B1/ko
Publication of WO2012113279A1 publication Critical patent/WO2012113279A1/zh
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16Z—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS, NOT OTHERWISE PROVIDED FOR
    • G16Z99/00—Subject matter not provided for in other main groups of this subclass
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04M—TELEPHONIC COMMUNICATION
    • H04M3/00—Automatic or semi-automatic exchanges
    • H04M3/22—Arrangements for supervision, monitoring or testing
    • H04M3/2236—Quality of speech transmission monitoring
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/08—Testing, supervising or monitoring using real traffic

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  • the present invention relates to the field of communications, and in particular, to a data processing method and device for loss of points. Background technique
  • the existing network evaluation system is more than the KPI (Key Performance Indicators) analysis of the network element, and the analysis system obtains the number of dropped calls, the call quality parameter, the success rate of the short message receiving, the average sending time of the short message, and the average sending time of the short message.
  • KPI Key Performance Indicators
  • Multiple data such as the access failure rate of the calling party, analyze and calculate the data, evaluate the network quality, analyze the network failure, and standardize the operation management of the network.
  • the ⁇ analysis system can obtain the user-perceived evaluation result.
  • the prior art does not provide the responsibility distribution of the user-perceived evaluation result, and does not assign the responsibility score in the evaluation result, which is not conducive to locating the user's perception related problem. Summary of the invention
  • the embodiment of the invention provides a data processing method and device for losing points, and realizes the responsibility distribution of the user perception evaluation result.
  • An embodiment of the present invention provides a data processing method for a loss of points, including: Determining a contribution of the characterization KPI to the QoE score according to the characterization KPI score; finding a correspondence between the characterization KPI and the factor, determining a contribution of the factor corresponding to the characterization KPI to the QoE score;
  • An embodiment of the present invention provides a data processing device for a loss of points, including: a processing unit, configured to determine a contribution of the characterization KPI to a QoE score according to a characterization KPI score, and find a correspondence between the characterization KPI and a factor , determining and characterizing
  • a summation unit for summing the contributions of the same factor to the QoE score, and obtaining the score of the same factor.
  • the embodiment of the invention has at least the following advantages:
  • the contribution of the factor corresponding to the KPI to the QoE score is determined according to the characterization of the KPI score, and then the factor is lost, thereby realizing the responsibility distribution of the user perception evaluation result.
  • FIG. 1 is a schematic diagram of an evaluation system perceived by a user in the prior art
  • FIG. 2 is a schematic diagram of an architecture for assigning responsibility for user-perceived evaluation results according to an embodiment of the present invention
  • FIG. 3 is a schematic flow chart of a data processing method for a factor loss according to an embodiment of the present invention.
  • FIG. 4 is a schematic diagram of a method for determining a proportion of responsibility for a voice service as an example in the embodiment of the present invention
  • FIG. 5 to FIG. 7 are schematic diagrams showing the structure of a data processing device with a loss of points according to an embodiment of the present invention. detailed description
  • the user-aware evaluation system is shown in Figure 1.
  • the real user experience is obtained by means of related data, KPI-KQK Key Quality Indicators, and QoE (Quality of Experience) layer-by-layer mapping.
  • the specific method is as follows: Firstly, through the calculation of the underlying related data, the scores of each characterization KPI are obtained; the scores of each characterization KPI are multiplied by their weights and summed to obtain the score of the upper corresponding KQI; according to the KQI score and its weight
  • the user's perceived sub-score score can be obtained from a certain angle, and finally the final QoE score perceived by the user is obtained according to the sub-item QoE score and weight.
  • the embodiment of the present invention provides a system structure for performing responsibility distribution on user-perceived evaluation results.
  • the architecture uses a voice service evaluation system as an example.
  • the data processing method for the missing points includes the following steps:
  • Step 301 The responsibility distribution device calculates the score of the KPI based on the score of the characterization KPI.
  • the responsible distribution device needs to obtain all the scores of the KPIs, that is, the characterization of the KPI 1 ⁇ characterization KPI n loss score shown in Figure 2.
  • Step 302 Calculate a contribution of the characterization KPI to the corresponding KQI score according to the characterization KPI score and its weight.
  • the corresponding KQI score contribution characterization KPI score *x.
  • X is the weight that characterizes the contribution of the KPI to the corresponding KQI, and the weight is calculated corresponding to the KPI. The weights at the time of the score are the same.
  • Step 303 Calculate a contribution of the KPI loss score to the sub-item QoE loss score according to the corresponding KQI weight.
  • the sub-item QoE lost contribution characterization KPI lost points * x * y.
  • x is the weight that characterizes the contribution of the KPI to the corresponding KQI score, the weight is consistent with the weight of the KPI in calculating the corresponding KQI score;
  • y is the weight of the corresponding KQI contribution to the sub-item QoE, and the corresponding KQI is calculated.
  • the weights of the QoE scores are the same.
  • Step 304 Calculate the contribution of the KPI score to the QoE score according to the sub-item QoE weight.
  • QoE lost contribution characterization KPI loss score *x*y*z.
  • x is the weight that characterizes the contribution of the KPI to the corresponding KQI score, the weight is consistent with the weight of the KPI in calculating the corresponding KQI score
  • y is the weight of the corresponding KQI contribution to the QoE score, and the corresponding KQI is calculated.
  • the weights of the QoE scores are consistent;
  • z is the weight of the corresponding QoE contribution to the QoE score, which is consistent with the weight of the corresponding KQI when calculating the score of the QoE.
  • the responsibility distribution device receives the contribution of each KPI loss to the QoE score.
  • the responsibility distribution equipment is characterized by KPI 1 ⁇ characterization KPI n contribution to QoE scores.
  • Step 305 Calculate the contribution of each factor to the QoE score based on the contribution of the KPI score to the QoE score and the factor ratio.
  • characterization KPI lost points * x * y * z * responsibility ratio.
  • X is the weight of the KPI contribution to the corresponding KQI score, and the weight is consistent with the weight of the KPI in calculating the corresponding KQI score;
  • y is the weight of the corresponding KQI contribution to the QoE score, and the corresponding KQI is calculated.
  • the weights of the QoE scores are consistent;
  • z is the weight of the corresponding QoE contribution to the QoE score, which is consistent with the weight of the corresponding KQI when calculating the score of the QoE.
  • the factor loss contribution of each evaluation dimension is obtained for each characterization KPI score.
  • the SQI Sound Quality Index
  • voice services Voice Quality Index
  • the proportion of responsibility for the SQI factor is determined as follows: For each factor, a counter is set, the counter is counted according to the result of the quantitative analysis of the factor representing the KPI, and the proportion of responsibility of each factor is determined according to the counting result of the counter. Specifically include:
  • the counter counts based on the results of the quantitative analysis of the factors that characterize the KPI. For example, suppose that the SQI score for characterizing a KPI is caused by network coverage. To increment the counter count value of the network overlay by one, the count values of the remaining counters are unchanged. When the SQI loss is attributed to network coverage and interference, the counters for network coverage and interference are incremented by 1 respectively, and the counters of the remaining factors are unchanged.
  • the second step is to calculate the proportion of responsibility for each factor.
  • the quantitative analysis of the factors that characterize the KPI includes: obtaining all the factors that can lead to the characterization of the KPI loss, and assigning the analysis results of all factors to the corresponding factors, and obtaining the cause of the KPI loss. For example, as shown in Figure 4, obtain all the factors that can cause the KPI to be scored, including network signal strength, network line conditions, and other factors that may cause the KPI to be scored, and then analyze the factors that cause the KPI to be scored, and These factors are again attributed to the cause: coverage or terminal.
  • Step 306 summing the factors of the missing points of the respective evaluation latitudes, and calculating the loss points of the respective factors.
  • the contribution of the factor corresponding to the KPI to the QoE score is determined according to the characterization of the KPI score, and then the factor is lost, thereby realizing the responsibility distribution of the user perception evaluation result.
  • the embodiment of the present invention further provides the following device embodiments.
  • An embodiment of the present invention provides a data processing device with a loss of points, as shown in FIG. 5, include:
  • the processing unit 11 is configured to determine a contribution of the characterization KPI to the QoE loss score according to the characterization KPI score, find a correspondence between the characterization KPI and the factor, and determine a factor corresponding to the characterization KPI that is lost to the QoE Contribution
  • the statistical unit 12 is configured to count the contribution of all the factors that represent the KPI loss score to the QoE loss score
  • the summation unit 13 is configured to sum the contributions of the same factor to the QoE score, and obtain the score of the same factor.
  • the processing unit 11 includes:
  • the first processing sub-unit 111 is configured to determine, according to the characterization KPI loss and weight, the contribution of the characterization KPI loss to the KQI score;
  • the second processing sub-unit 112 is configured to determine, according to the contribution of the characterization KPI score to the KQI score and the weight, the contribution of the characterization KPI loss score to the sub-item QoE score;
  • the third processing sub-unit 113 is configured to determine, according to the contribution of the characterization KPI score to the sub-item QoE score and the weight, the contribution of the characterization KPI score to the QoE score.
  • the processing unit 11 includes:
  • the fourth processing sub-unit 114 is configured to calculate, according to the factor responsibility ratio of the factor corresponding to the characterization KPI, the contribution of each factor to the QoE loss.
  • the processing unit 11 further includes:
  • the counting sub-unit 115 is configured to count the factors causing the characterization of the KPI loss according to the factor analysis result of the characterization of the KPI loss score; and calculate the factor responsibility ratio according to the counting result of the factor causing the characterization of each KPI loss.
  • the processing unit 11 further includes:
  • the factor analysis unit 116 is used to obtain all the factors that can cause the characterization of the KPI to be scored, and the analysis result of all the factors is attributed to the corresponding factor, and the factor causing the characterization of the KPI loss is obtained.
  • the device further includes:
  • the receiving unit 14 is configured to receive a characterization KPI score
  • a determining unit 15 configured to determine, according to the characterization KPI score, the characterization KPI loss.
  • the contribution of the factor corresponding to the characterization KPI to the QoE score is determined, and then the factor is lost, thereby realizing the responsibility distribution of the user perception evaluation result.
  • the present invention can be implemented by means of software plus a necessary general hardware platform, and of course, can also be through hardware, but in many cases, the former is a better implementation. the way.
  • the technical solution of the present invention which is essential or contributes to the prior art, may be embodied in the form of a software product stored in a storage medium, including a plurality of instructions for making a A computer device (which may be a personal computer, server, or network device, etc.) performs the methods described in various embodiments of the present invention.
  • modules in the apparatus in the embodiments may be distributed in the apparatus of the embodiment according to the description of the embodiments, or may be correspondingly changed in one or more apparatuses different from the embodiment.
  • the modules of the above embodiments may be combined into one module, or may be further split into a plurality of sub-modules.

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Abstract

本发明实施例公开了一种要因失分的数据处理方法及设备，该方法包括：根据表征KPI失分确定所述表征KPI对QoE失分的贡献；查找所述表征KPI与要因的对应关系，确定与所述表征KPI对应的要因对所述QoE失分的贡献；统计所有表征KPI失分对应的要因对所述QoE失分的贡献；将同一要因对所述QoE失分的贡献求和，得到所述同一要因的失分。本发明实施例中，根据表征KPI失分确定与表征KPI对应的要因对QoE失分的贡献，进而得到要因失分，从而实现了对用户感知评价结果的责任分配。

Description

要因失分的数据处理方法及设备 本申请要求以下中国专利申请的优先权：
于 2011年 2月 24曰提交中国专利局，申请号为 201110044494.X, 发明名称为 "要因失分的数据处理方法及设备" 的中国专利申请。 技术领域
本发明涉及通信领域，尤其涉及一种要因失分的数据处理方法及 设备。 背景技术
随着通信市场用户数的高速增长， 通信运营商间的竟争日益激 烈， 成熟的电信运营商在关心自身网络稳定运行的同时， 如何提高用 户满意度， 降低用户流失率， 挖掘用户的潜在价值和利润增长点， 已 经成为了保持竟争优势和争夺未来市场领导地位的关键。现有的网络 评价体系多 ^^于网元的 KPI ( Key Performance Indicators , 关键性能 指标）分析， ΚΡΙ分析系统从网络服务器获取掉话次数、 通话质量参 数、 短信接收成功率、 短信平均发送时长、 主叫接入失败率等多个数 据， 对这些数据进行分析运算， 评价网络质量， 分析网络故障， 规范 网络的运营管理。
ΚΡΙ分析系统能够获得用户感知评价结果， 但是， 现有技术中没 有提供对用户感知评价结果的责任分配，没有将评估结果中的失分进 行责任分配， 不利于定位用户感知相关问题。 发明内容
本发明实施例提供了一种要因失分的数据处理方法及设备，实现 了对用户感知评价结果的责任分配。
本发明实施例提供了一种要因失分的数据处理方法， 包括： 根据表征 KPI失分确定所述表征 KPI对 QoE失分的贡献； 查找所述表征 KPI与要因的对应关系， 确定与所述表征 KPI对 应的要因对所述 QoE失分的贡献；
统计所有表征 KPI失分对应的要因对所述 QoE失分的贡献； 将同一要因对所述 QoE失分的贡献求和， 得到所述同一要因的 失分。
本发明实施例提供了一种要因失分的数据处理设备， 包括： 处理单元， 用于根据表征 KPI失分确定所述表征 KPI对 QoE失 分的贡献， 查找所述表征 KPI 与要因的对应关系， 确定与所述表征
KPI对应的要因对所述 QoE失分的贡献；
统计单元， 用于统计所有表征 KPI失分对应的要因对所述 QoE 失分的贡献；
求和单元， 用于将同一要因对所述 QoE失分的贡献求和， 得到 所述同一要因的失分。
与现有技术相比， 本发明实施例至少具有以下优点：
本发明实施例中， 根据表征 KPI失分确定与表征 KPI对应的要 因对 QoE失分的贡献， 进而得到要因失分， 从而实现了对用户感知 评价结果的责任分配。 附图说明
图 1是现有技术中用户感知的评价系统示意图；
图 2是本发明实施例提供的对用户感知评价结果进行责任分配 的体系结构示意图；
图 3 是本发明实施例提供的要因失分的数据处理方法的流程示 意图；
图 4是本发明实施例中以语音业务为例要因的责任比例的确定 方式示意图；
图 5~图 7是本发明实施例提供的要因失分的数据处理设备的结 构示意图。 具体实施方式
下面将结合本发明的实施例中的附图，对本发明的实施例中的技 术方案进行清楚、 完整地描述， 显然， 下面所描述的实施例仅仅是本 发明一部分实施例， 而不是全部的实施例。 基于本发明中的实施例， 本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其 他实施例， 都属于本发明的实施例保护的范围。
用户感知的评价系统如图 1所示，真实用户感受是由相关数据一 表征 KPI— KQK Key Quality Indicators,关键质量指标）一 QoE( Quality of Experience, 体验质量）逐层映射的方式得到的。 具体的方法如下： 首先通过对底层相关数据的计算，获得各项表征 KPI的得分； 将各项 表征 KPI的得分与其权重相乘并求和， 得到上层对应 KQI的得分； 根据 KQI得分及其权重， 可以得到用户在某个角度的感知分项得分， 最终根据这些分项 QoE得分及权重，得到用户感知的最终 QoE得分。
本发明实施例提供一种对用户感知评价结果进行责任分配的体 系结构， 如图 2所示， 该体系结构以语音业务评估体系为例。 结合图 2所示的体系结构， 要因失分的数据处理方法， 如图 3所示， 包括以 下步骤：
步骤 301 ,责任分配设备根据表征 KPI的得分计算出该 KPI的失 分。
具体的， 表征 KPI失分为： 表征 KPI失分 =表征 KPI满分 -表 征 KPI得分。
本步骤中责任分配设备需要得到所有表征 KPI 的失分， 即图 2 所示的表征 KPI 1~表征 KPI n的失分。
步骤 302, 根据表征 KPI失分及其权重计算出表征 KPI对相应 KQI失分的贡献。
具体的， 相应 KQI失分贡献=表征 KPI失分 *x。 其中， X为表征 KPI对相应 KQI失分贡献的权重， 该权重与该 KPI在计算相应 KQI 得分时的权重一致。
步骤 303, 根据相应 KQI权重计算出表征 KPI失分对分项 QoE 失分的贡献。
具体的， 分项 QoE失分贡献=表征 KPI失分 *x*y。 其中， x为表 征 KPI对相应 KQI失分贡献的权重，该权重与该 KPI在计算相应 KQI 得分时的权重一致； y为相应 KQI对分项 QoE失分贡献的权重， 与 相应 KQI在计算分项 QoE得分时的权重一致。
步骤 304, 根据分项 QoE权重计算出表征 KPI失分对 QoE失分 的贡献。
具体的， QoE失分贡献=表征 KPI失分 *x*y*z。 其中， x为表征 KPI对相应 KQI失分贡献的权重， 该权重与该 KPI在计算相应 KQI 得分时的权重一致； y为相应 KQI对分项 QoE失分贡献的权重， 与 相应 KQI在计算分项 QoE得分时的权重一致； z为相应分项 QoE对 QoE失分贡献的权重， 与相应 KQI在计算分项 QoE得分时的权重一 致。
经过本步骤， 责任分配设备得到各个 KPI失分分别对 QoE失分 的贡献。 结合图 2所示， 责任分配设备得到表征 KPI 1~表征 KPI n分 别对 QoE失分的贡献。
步骤 305, 根据表征 KPI失分对 QoE失分的贡献及要因责任比 例， 计算得到各个要因对 QoE失分的贡献。
具体的， 要因失分贡献 =表征 KPI失分 *x*y*z*责任比例。 其中， X为表征 KPI对相应 KQI失分贡献的权重， 该权重与该 KPI在计算 相应 KQI得分时的权重一致； y为相应 KQI对分项 QoE失分贡献的 权重， 与相应 KQI在计算分项 QoE得分时的权重一致； z为相应分 项 QoE对 QoE失分贡献的权重， 与相应 KQI在计算分项 QoE得分 时的权重一致。结合图 2所示，针对每一表征 KPI失分分别得到各个 评价维度的要因失分贡献。
其中， 各个要因的责任比例按照下述方式确定：
如图 4所示， 以语音业务表征 KPI的 SQI ( Speech Quality Index, 话音质量指数） 为例， SQI的要因的责任比例的确定方式如下： 针对每种要因设置计数器，该计数器根据表征 KPI的要因量化分 析结果进行计数， 根据计数器的计数结果确定各个要因的责任比例， 具体包括：
第一步， 计数器根据表征 KPI的要因量化分析结果进行计数。 例如， 假定表征 KPI的 SQI失分是由网络覆盖导致的， 要因网 络覆盖的计数器计数值加 1 , 其余计数器的计数值不变。 当 SQI失分 原因归结到网络覆盖和干扰时，则要因网络覆盖和干扰的计数器分别 加 1 , 其余要因的计数器不变。
第二步， 计算各个要因的责任比例。
要因的责任比例用 A表示， 某要因的计数器计数结果为 Y, 所 有要因的计数器计数结果之和为 Z, 则该要因的责任比例 A=Y/Z。
其中， 表征 KPI 的要因量化分析包括： 获取能够导致表征 KPI 失分的所有因素， 将对所有因素的分析结果归属到对应的要因， 得到 导致表征 KPI失分的要因。 例如， 如图 4所示， 获取能够导致表征 KPI失分的所有因素， 包括网络信号强度、 网络线路状况等所有可能 导致表征 KPI失分的因素， 然后分析导致表征 KPI失分的因素， 并 将这些因素再归属到要因： 覆盖或者终端。
步骤 306, 对各个评价纬度的要因失分贡献求和， 计算出各个要 因的失分。
具体的， 要因失分=各纬度该要因失分贡献求和。
结合图 2所示， 以终端质量责任分为例， 则终端责任分 =∑ 各 纬度终端失分。
本发明实施例中， 根据表征 KPI失分确定与表征 KPI对应的要 因对 QoE失分的贡献， 进而得到要因失分， 从而实现了对用户感知 评价结果的责任分配。
基于与上述方法实施例相同的技术构思，本发明实施例还提供下 述装置实施例。
本发明实施例提供一种要因失分的数据处理设备， 如图 5所示， 包括：
处理单元 11 , 用于根据表征 KPI失分确定所述表征 KPI对 QoE 失分的贡献， 查找所述表征 KPI与要因的对应关系，确定与所述表征 KPI对应的要因对所述 QoE失分的贡献；
统计单元 12,用于统计所有表征 KPI失分对应的要因对所述 QoE 失分的贡献；
求和单元 13, 用于将同一要因对所述 QoE失分的贡献求和， 得 到所述同一要因的失分。
如图 6所示， 所述处理单元 11包括：
第一处理子单元 111 , 用于根据表征 KPI失分及权重确定所述表 征 KPI失分对 KQI失分的贡献；
第二处理子单元 112,用于根据所述表征 KPI失分对 KQI失分的 贡献及权重确定所述表征 KPI失分对分项 QoE失分的贡献；
第三处理子单元 113, 用于根据所述表征 KPI失分对分项 QoE 失分的贡献及权重确定所述表征 KPI失分对 QoE失分的贡献。
所述处理单元 11包括：
第四处理子单元 114, 用于根据与所述表征 KPI对应的要因的要 因责任比例， 计算得到各个要因对所述 QoE失分的贡献。
所述处理单元 11还包括：
计数子单元 115, 用于根据表征 KPI失分的要因量化分析结果对 导致所述表征 KPI 失分的要因进行计数； 根据对导致各个表征 KPI 失分的要因的计数结果计算得到要因责任比例。
所述处理单元 11还包括：
要因分析子单元 116, 用于获取能够导致所述表征 KPI失分的所 有因素， 将对所述所有因素的分析结果归属到对应的要因， 得到导致 所述表征 KPI失分的要因。
如图 7所示， 该设备还包括：
接收单元 14, 用于接收表征 KPI得分；
确定单元 15, 用于根据所述表征 KPI得分确定所述表征 KPI失 本发明实施例中， 根据表征 KPI失分确定与表征 KPI对应的要 因对 QoE失分的贡献， 进而得到要因失分， 从而实现了对用户感知 评价结果的责任分配。
通过以上的实施方式的描述，本领域的技术人员可以清楚地了解 到本发明可借助软件加必需的通用硬件平台的方式来实现， 当然也可 以通过硬件，但很多情况下前者是更佳的实施方式。基于这样的理解， 本发明的技术方案本质上或者说对现有技术做出贡献的部分可以以 软件产品的形式体现出来， 该计算机软件产品存储在一个存储介质 中， 包括若干指令用以使得一台计算机设备（可以是个人计算机， 服 务器， 或者网络设备等）执行本发明各个实施例所述的方法。
本领域技术人员可以理解附图只是一个优选实施例的示意图，附 图中的模块或流程并不一定是实施本发明所必须的。
本领域技术人员可以理解实施例中的装置中的模块可以按照实 施例描述进行分布于实施例的装置中，也可以进行相应变化位于不同 于本实施例的一个或多个装置中。上述实施例的模块可以合并为一个 模块， 也可以进一步拆分成多个子模块。
上述本发明实施例序号仅仅为了描述， 不代表实施例的优劣。 以上公开的仅为本发明的几个具体实施例， 但是， 本发明并非局 限于此，任何本领域的技术人员能思之的变化都应落入本发明的保护 范围。

Claims

权利要求
1、 一种要因失分的数据处理方法， 其特征在于， 包括： 根据表征 KPI失分确定所述表征 KPI对 QoE失分的贡献； 查找所述表征 KPI与要因的对应关系， 确定与所述表征 KPI对 应的要因对所述 QoE失分的贡献；
统计所有表征 KPI失分对应的要因对所述 QoE失分的贡献； 将同一要因对所述 QoE失分的贡献求和， 得到所述同一要因的 失分。
2、 如权利要求 1所述的方法， 其特征在于， 所述根据表征 KPI 失分确定所述表征 KPI对 QoE失分的贡献包括：
根据表征 KPI失分及权重确定所述表征 KPI失分对 KQI失分的 贡献；
根据所述表征 KPI失分对 KQI失分的贡献及权重确定所述表征 KPI失分对分项 QoE失分的贡献；
根据所述表征 KPI失分对分项 QoE失分的贡献及权重确定所述 表征 KPI失分对 QoE失分的贡献。
3、 如权利要求 1所述的方法， 其特征在于， 所述确定与所述表 征 KPI对应的要因对所述 QoE失分的贡献包括：
根据与所述表征 KPI对应的要因的要因责任比例，计算得到各个 要因对所述 QoE失分的贡献。
4、 如权利要求 3所述的方法， 其特征在于， 所述要因责任比例 通过下述方式得到：
设置与各个要因对应的计数器；
对表征 KPI 失分进行要因量化分析结果， 对导致所述表征 KPI 失分的要因由所述计数器进行计数；
根据各个计数器的计数结果计算得到要因的要因责任比例。
5、 如权利要求 1所述的方法， 其特征在于， 所述对表征 KPI失 分进行要因量化分析结果包括： 获取能够导致所述表征 KPI失分的所有因素；
将对所述所有因素的分析结果归属到对应的要因，得到导致所述 表征 KPI失分的要因。
6、 如权利要求 1所述的方法， 其特征在于， 所述根据表征 KPI 失分确定所述表征 KPI对 QoE失分的贡献之前， 还包括：
接收表征 KPI得分并根据所述表征 KPI得分确定所述表征 KPI 失分。
7、 一种要因失分的数据处理设备， 其特征在于， 包括： 处理单元， 用于根据表征 KPI失分确定所述表征 KPI对 QoE失 分的贡献， 查找所述表征 KPI 与要因的对应关系， 确定与所述表征 KPI对应的要因对所述 QoE失分的贡献；
统计单元， 用于统计所有表征 KPI失分对应的要因对所述 QoE 失分的贡献；
求和单元， 用于将同一要因对所述 QoE失分的贡献求和， 得到 所述同一要因的失分。
8、 如权利要求 7所述的设备， 其特征在于， 所述处理单元包括： 第一处理子单元， 用于根据表征 KPI 失分及权重确定所述表征
KPI失分对 KQI失分的贡献；
第二处理子单元， 用于根据所述表征 KPI失分对 KQI失分的贡 献及权重确定所述表征 KPI失分对分项 QoE失分的贡献；
第三处理子单元， 用于根据所述表征 KPI失分对分项 QoE失分 的贡献及权重确定所述表征 KPI失分对 QoE失分的贡献。
9、 如权利要求 7所述的设备， 其特征在于， 所述处理单元包括： 第四处理子单元，用于根据与所述表征 KPI对应的要因的要因责 任比例， 计算得到各个要因对所述 QoE失分的贡献。
10、 如权利要求 9所述的设备， 其特征在于， 所述处理单元还包 括：
计数子单元，用于根据表征 KPI失分的要因量化分析结果对导致 所述表征 KPI失分的要因进行计数； 根据对导致各个表征 KPI失分 的要因的计数结果计算得到要因责任比例。
11、 如权利要求 9所述的设备， 其特征在于， 所述处理单元还包 括：
要因分析子单元，用于获取能够导致所述表征 KPI失分的所有因 素， 将对所述所有因素的分析结果归属到对应的要因， 得到导致所述 表征 KPI失分的要因。
12、 如权利要求 7所述的设备， 其特征在于， 还包括：
接收单元， 用于接收表征 KPI得分；
确定单元， 用于根据所述表征 KPI得分确定所述表征 KPI失分。
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