TWI815627B - Electronic device and method for determining customer complaint handling decision of user equipment - Google Patents

Electronic device and method for determining customer complaint handling decision of user equipment Download PDF

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TWI815627B
TWI815627B TW111132225A TW111132225A TWI815627B TW I815627 B TWI815627 B TW I815627B TW 111132225 A TW111132225 A TW 111132225A TW 111132225 A TW111132225 A TW 111132225A TW I815627 B TWI815627 B TW I815627B
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user equipment
base station
customer complaint
customer
signal data
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TW202410712A (en
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涂耀中
趙欣杰
許長裕
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中華電信股份有限公司
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Abstract

An electronic device and a method for determining a customer complaint handling decision of a user equipment are provided. The method includes: receiving a customer complaint user equipment signal data corresponding to a customer complaint user equipment; receiving a reference user equipment signal data corresponding to a reference user equipment; receiving a base station data corresponding to a base station; receiving a reference base station data corresponding to a reference base station; and input the customer complaint user equipment signal data, the reference user equipment signal data, the base station data and the reference base station data into at least one machine learning model to determine a customer complaint handling decision corresponding to the customer complaint user equipment.

Description

決定用戶設備的客訴處理決策的電子裝置及方法Electronic device and method for determining customer complaint handling decisions for user equipment

本發明是有關於一種決定用戶設備的客訴處理決策的電子裝置及方法。The present invention relates to an electronic device and method for determining customer complaint handling decisions of user equipment.

由於電信公司的用戶數量眾多，當用戶使用電信公司佈建的行動網路發生問題而向電信公司提出客訴時，電信公司往往無法即時地找出問題原因並加以解決，從而導致電信公司無法即時地解決用戶需求。Due to the large number of users of telecommunications companies, when users have problems using the mobile networks deployed by the telecommunications companies and file customer complaints with the telecommunications companies, the telecommunications companies are often unable to immediately find out the cause of the problem and solve it. As a result, the telecommunications companies cannot immediately Solve user needs effectively.

本發明提供一種決定用戶設備的客訴處理決策的電子裝置及方法，可讓行動網路的管理者在接收到用戶的客訴時，能更有效率地決定出客訴處理決策。The present invention provides an electronic device and method for determining customer complaint handling decisions for user equipment, which allows mobile network managers to more efficiently decide on customer complaint handling decisions when receiving user complaints.

本發明的決定用戶設備的客訴處理決策的電子裝置包括儲存媒體、收發器以及處理器。儲存媒體儲存多個模組。收發器通訊連接至客訴用戶設備、參考用戶設備、基地台以及參考基地台。處理器耦接儲存媒體以及收發器，並且存取和執行多個模組，其中多個模組包括：客訴用戶設備訊號資料接收模組，通過收發器接收對應於客訴用戶設備的客訴用戶設備訊號資料；參考用戶設備訊號資料接收模組，通過收發器接收對應於參考用戶設備的參考用戶設備訊號資料；基地台資料接收模組，通過收發器接收對應於基地台的基地台資料；參考基地台資料接收模組，通過收發器接收對應於參考基地台的參考基地台資料；以及客訴處理決策決定模組，將客訴用戶設備訊號資料、參考用戶設備訊號資料、基地台資料以及參考基地台資料輸入至至少一機器學習模型以決定對應於客訴用戶設備的客訴處理決策。The electronic device of the present invention that determines customer complaint handling decisions of user equipment includes a storage medium, a transceiver, and a processor. Storage media stores multiple modules. The transceiver communication is connected to the customer user equipment, the reference user equipment, the base station and the reference base station. The processor is coupled to the storage medium and the transceiver, and accesses and executes a plurality of modules. The plurality of modules include: a customer equipment signal data receiving module, which receives customer information corresponding to the customer equipment through the transceiver. User equipment signal data; the reference user equipment signal data receiving module receives the reference user equipment signal data corresponding to the reference user equipment through the transceiver; the base station data receiving module receives the base station data corresponding to the base station through the transceiver; The reference base station data receiving module receives the reference base station data corresponding to the reference base station through the transceiver; and the customer complaint processing decision-making module combines the customer complaint user equipment signal data, reference user equipment signal data, base station data and The reference base station data is input into at least one machine learning model to determine a customer complaint handling decision corresponding to the customer complaint user equipment.

本發明的決定用戶設備的客訴處理決策的方法包括：接收對應於客訴用戶設備的客訴用戶設備訊號資料；接收對應於參考用戶設備的參考用戶設備訊號資料；接收對應於基地台的基地台資料；接收對應於參考基地台的參考基地台資料；以及將客訴用戶設備訊號資料、參考用戶設備訊號資料、基地台資料以及參考基地台資料輸入至至少一機器學習模型以決定對應於客訴用戶設備的客訴處理決策。The method of determining the customer complaint handling decision of the user equipment of the present invention includes: receiving the customer complaint user equipment signal data corresponding to the customer complaint user equipment; receiving the reference user equipment signal data corresponding to the reference user equipment; receiving the base station corresponding to the base station. station data; receiving reference base station data corresponding to the reference base station; and inputting the customer user equipment signal data, the reference user equipment signal data, the base station data and the reference base station data into at least one machine learning model to determine the data corresponding to the customer base station. Complaint handling decisions for user equipment.

圖1是根據本發明的一實施例繪示的一種決定用戶設備的客訴處理決策的電子裝置100的示意圖。電子裝置100可包括儲存媒體110、收發器120以及處理器130。FIG. 1 is a schematic diagram of an electronic device 100 that determines customer complaint handling decisions for user equipment according to an embodiment of the present invention. The electronic device 100 may include a storage medium 110, a transceiver 120, and a processor 130.

儲存媒體110例如是任何型態的固定式或可移動式的隨機存取記憶體（random access memory，RAM）、唯讀記憶體（read-only memory，ROM）、快閃記憶體（flash memory）、硬碟（hard disk drive，HDD）、固態硬碟（solid state drive，SSD）或類似元件或上述元件的組合，而用於儲存可由處理器130執行的多個模組或各種應用程式。在本實施例中，儲存媒體110可儲存客訴用戶設備訊號資料接收模組111、參考用戶設備訊號資料接收模組112、基地台資料接收模組113、參考基地台資料接收模組114以及客訴處理決策決定模組115。在其它實施例中，儲存媒體110還可儲存機器學習模型訓練模組116。此些模組的功能將於後續說明。The storage medium 110 is, for example, any type of fixed or removable random access memory (random access memory, RAM), read-only memory (read-only memory, ROM), or flash memory (flash memory). , hard disk drive (HDD), solid state drive (SSD) or similar components or a combination of the above components, and are used to store multiple modules or various application programs that can be executed by the processor 130 . In this embodiment, the storage medium 110 can store the customer user equipment signal data receiving module 111, the reference user equipment signal data receiving module 112, the base station data receiving module 113, the reference base station data receiving module 114, and the customer v. Processing decision decision module 115. In other embodiments, the storage medium 110 may also store the machine learning model training module 116 . The functions of these modules will be explained later.

收發器120以無線或有線的方式傳送及接收訊號。收發器120可通訊連接至客訴用戶設備200、參考用戶設備300a、參考用戶設備300b、基地台400、參考基地台500a以及參考基地台500b。在此需說明的是，圖1所示的參考用戶設備的數量及參考基地台的數量僅為示意，本發明不對此限制。為了方便說明，後續實施例將以圖1繼續說明。The transceiver 120 transmits and receives signals in a wireless or wired manner. The transceiver 120 can be communicatively connected to the customer user equipment 200, the reference user equipment 300a, the reference user equipment 300b, the base station 400, the reference base station 500a and the reference base station 500b. It should be noted here that the number of reference user equipment and the number of reference base stations shown in Figure 1 are only for illustration, and the present invention is not limited thereto. For convenience of explanation, subsequent embodiments will continue to be described with reference to FIG. 1 .

處理器130例如是中央處理單元（central processing unit，CPU），或是其他可程式化之一般用途或特殊用途的微控制單元（micro control unit，MCU）、微處理器（microprocessor）、數位信號處理器（digital signal processor，DSP）、可程式化控制器、特殊應用積體電路（application specific integrated circuit，ASIC）、圖形處理器（graphics processing unit，GPU）、影像訊號處理器（image signal processor，ISP）、影像處理單元（image processing unit，IPU）、算數邏輯單元（arithmetic logic unit，ALU）、複雜可程式邏輯裝置（complex programmable logic device，CPLD）、現場可程式化邏輯閘陣列（field programmable gate array，FPGA）或其他類似元件或上述元件的組合。處理器130可耦接至儲存媒體110以及收發器120，並且存取和執行儲存於儲存媒體110中的多個模組和各種應用程式。The processor 130 is, for example, a central processing unit (CPU), or other programmable general-purpose or special-purpose micro control unit (MCU), microprocessor, or digital signal processing unit. Digital signal processor (DSP), programmable controller, application specific integrated circuit (ASIC), graphics processing unit (GPU), image signal processor (ISP) ), image processing unit (IPU), arithmetic logic unit (ALU), complex programmable logic device (CPLD), field programmable gate array (field programmable gate array) , FPGA) or other similar components or a combination of the above components. The processor 130 can be coupled to the storage medium 110 and the transceiver 120, and access and execute multiple modules and various applications stored in the storage medium 110.

在一實施例中，客訴用戶設備200可通訊連接至基地台400。進一步而言，參考用戶設備300a可通訊連接至基地台400，且參考用戶設備300b可通訊連接至基地台400，然而本發明不限於此。在其它實施例中，參考用戶設備300a與客訴用戶設備200的距離小於預設門檻值，且參考用戶設備300b與客訴用戶設備200的距離小於此預設門檻值。In one embodiment, the customer equipment 200 can be communicatively connected to the base station 400. Furthermore, the reference user equipment 300a can be communicatively connected to the base station 400, and the reference user equipment 300b can be communicatively connected to the base station 400, but the present invention is not limited thereto. In other embodiments, the distance between the reference user equipment 300a and the customer user equipment 200 is less than a preset threshold, and the distance between the reference user equipment 300b and the customer user equipment 200 is less than the preset threshold.

在一實施例中，參考基地台500a與基地台400的距離小於距離門檻值，且參考基地台500b與基地台400的距離小於此距離門檻值。然而本發明不限於此。In one embodiment, the distance between the reference base station 500a and the base station 400 is less than the distance threshold, and the distance between the reference base station 500b and the base station 400 is less than the distance threshold. However, the present invention is not limited to this.

圖2是根據本發明的一實施例繪示的一種決定用戶設備的客訴處理決策的方法的流程圖。請同時參照圖1及圖2，本實施例的方法適用於圖1所示的電子裝置100。以下即搭配電子裝置100說明本發明之決定用戶設備的客訴處理決策的方法的詳細步驟。FIG. 2 is a flow chart illustrating a method for determining customer complaint handling decisions for user equipment according to an embodiment of the present invention. Please refer to FIG. 1 and FIG. 2 at the same time. The method of this embodiment is applicable to the electronic device 100 shown in FIG. 1 . The following describes the detailed steps of the method for determining customer complaint handling decisions for user equipment according to the present invention in conjunction with the electronic device 100 .

在步驟S201中，客訴用戶設備訊號資料接收模組111可通過收發器120接收對應於客訴用戶設備200的客訴用戶設備訊號資料。在一實施例中，客訴用戶設備訊號資料可包括平均訊號強度、平均速率、最大速率以及最小速率，然而本發明不限於此。表1是客訴用戶設備200的客訴用戶設備訊號資料的一個範例。在其它實施例中，客訴用戶設備訊號資料接收模組111還可對客訴用戶設備訊號資料去識別化。 表1 客訴用戶設備200的客訴用戶設備訊號資料 平均訊號強度（dBm） 平均速率（Mbps） 最大速率（Mbps） 最小速率（Mbps） -97.58 24.06 113.35 1.19 In step S201, the customer complaint user equipment signal data receiving module 111 may receive the customer complaint user equipment signal data corresponding to the customer complaint user equipment 200 through the transceiver 120. In one embodiment, the user equipment signal data reported by the customer may include average signal strength, average rate, maximum rate, and minimum rate, but the invention is not limited thereto. Table 1 is an example of customer user equipment signal data of the customer user equipment 200 . In other embodiments, the customer complaint user equipment signal data receiving module 111 can also de-identify the customer complaint user equipment signal data. Table 1 Customer-complaint user equipment signal data of customer-complaint user equipment 200 Average signal strength (dBm) Average speed (Mbps) Maximum rate (Mbps) Minimum rate (Mbps) -97.58 24.06 113.35 1.19

在步驟S202中，參考用戶設備訊號資料接收模組112可通過收發器120接收對應於參考用戶設備300a及參考用戶設備300b的參考用戶設備訊號資料。在一實施例中，參考用戶設備訊號資料可包括平均訊號強度、訊號強度標準差、平均速率、速率標準差、平均最大速率、最大速率標準差、平均最小速率以及最小速率標準差，然而本發明不限於此。表2是參考用戶設備300a以及參考用戶設備300b的參考用戶設備訊號資料的一個範例。 表2 參考用戶設備300a以及參考用戶設備300b的參考用戶設備訊號資料 平均訊號強度（dBm） 訊號強度標準差 平均速率（Mbps） 速率標準差 平均最大速率 （Mbps） 最大速率標準差 平均最小速率（Mbps） 最小速率標準差 -72.44 14.11 55.65 15.43 140.15 20.32 3.83 1.88 In step S202, the reference user equipment signal data receiving module 112 may receive the reference user equipment signal data corresponding to the reference user equipment 300a and the reference user equipment 300b through the transceiver 120. In one embodiment, the reference user equipment signal data may include average signal strength, signal strength standard deviation, average rate, rate standard deviation, average maximum rate, maximum rate standard deviation, average minimum rate, and minimum rate standard deviation. However, the present invention Not limited to this. Table 2 is an example of reference user equipment signal data of the reference user equipment 300a and the reference user equipment 300b. Table 2 Reference user equipment signal data of reference user equipment 300a and reference user equipment 300b Average signal strength (dBm) Signal strength standard deviation Average speed (Mbps) rate standard deviation Average maximum speed (Mbps) Maximum rate standard deviation Average minimum rate (Mbps) Minimum rate standard deviation -72.44 14.11 55.65 15.43 140.15 20.32 3.83 1.88

在步驟S203中，基地台資料接收模組113可通過收發器120接收對應於基地台400的基地台資料。在一實施例中，基地台資料可包括基地台告警訊息以及基地台障礙歷史紀錄，然而本發明不限於此。表3是基地台400的基地台資料的一個範例。 表3 基地台400的基地台資料 基地台告警訊息 基地台障礙歷史紀錄 倒台告警訊息 1. 天線參數調整 2. 基地台維護施工 In step S203, the base station data receiving module 113 may receive base station data corresponding to the base station 400 through the transceiver 120. In one embodiment, the base station data may include base station alarm messages and base station failure history records, but the invention is not limited thereto. Table 3 is an example of base station information of base station 400. Table 3 Base station information of base station 400 Base station alarm message Base station obstruction history Downfall warning message 1. Antenna parameter adjustment 2. Base station maintenance and construction

在步驟S204中，參考基地台資料接收模組114可通過收發器120接收對應於參考基地台500a以及參考基地台500b的參考基地台資料。在一實施例中，參考基地台資料可包括基地台告警訊息以及基地台障礙歷史紀錄，然而本發明不限於此。表4是參考基地台500a以及參考基地台500b的參考基地台資料的一個範例。 表4 參考基地台500a以及參考基地台500b的參考基地台資料 基地台告警訊息 基地台障礙歷史紀錄 參考基地台500a 無 基地台傳輸障礙 參考基地台500b 無 基地台硬體障礙 In step S204, the reference base station data receiving module 114 may receive the reference base station data corresponding to the reference base station 500a and the reference base station 500b through the transceiver 120. In one embodiment, the reference base station data may include base station alarm messages and base station obstacle history records, but the invention is not limited thereto. Table 4 is an example of reference base station information of the reference base station 500a and the reference base station 500b. Table 4 Reference base station information of reference base station 500a and reference base station 500b Base station alarm message Base station obstruction history Reference base station 500a without Base station transmission obstruction Reference base station 500b without Base station hardware obstacles

在步驟S205中，客訴處理決策決定模組115可將客訴用戶設備訊號資料、參考用戶設備訊號資料、基地台資料以及參考基地台資料輸入至至少一機器學習模型以決定對應於客訴用戶設備200的客訴處理決策。在一實施例中，所述至少一機器學習模型可包括隨機森林模型（Random Forest Model）、梯度提升樹模型（Gradient Boost Tree Model）及神經網路模型（Neural Network Model），然而本發明不限於此。舉例來說，客訴處理決策決定模組115可將客訴用戶設備訊號資料、參考用戶設備訊號資料、基地台資料以及參考基地台資料輸入至隨機森林模型以獲得第一客訴處理決策的機率1以及第二客訴處理決策的機率2，且輸入至梯度提升樹模型以獲得第一客訴處理決策的機率3以及第二客訴處理決策的機率4，且輸入至神經網路模型以獲得第一客訴處理決策的機率5以及第二客訴處理決策的機率6。接著，客訴處理決策決定模組115可計算機率1、機率3以及機率5的平均值以獲得對應於第一客訴處理決策的第一平均機率，且可計算機率2、機率4以及機率6的平均值以獲得對應於第二客訴處理決策的第二平均機率。若第一平均機率大於第二平均機率，則客訴處理決策決定模組115可將第一客訴處理決策決定為對應於客訴用戶設備200的客訴處理決策。舉例來說，客訴處理決策例如是「立即派工維護基地台400」。In step S205, the customer complaint processing decision-making module 115 can input the customer complaint user equipment signal data, the reference user equipment signal data, the base station data, and the reference base station data into at least one machine learning model to determine the appropriate response to the customer complaint user. Customer complaint handling decision of device 200. In one embodiment, the at least one machine learning model may include a Random Forest Model, a Gradient Boost Tree Model, and a Neural Network Model. However, the invention is not limited to this. For example, the customer complaint handling decision-making module 115 can input the customer complaint user equipment signal data, the reference user equipment signal data, the base station data, and the reference base station data into the random forest model to obtain the probability of the first customer complaint handling decision. 1 and the probability 2 of the second customer complaint handling decision, and are input to the gradient boosting tree model to obtain the probability 3 of the first customer complaint handling decision and the probability 4 of the second customer complaint handling decision, and are input to the neural network model to obtain The probability of the first customer complaint handling decision is 5 and the probability of the second customer complaint handling decision is 6. Next, the customer complaint handling decision-making module 115 can calculate the average of probability 1, probability 3, and probability 5 to obtain the first average probability corresponding to the first customer complaint handling decision, and can calculate probability 2, probability 4, and probability 6. The average value is obtained to obtain the second average probability corresponding to the second customer complaint handling decision. If the first average probability is greater than the second average probability, the customer complaint handling decision-making module 115 may determine the first customer complaint handling decision as a customer complaint handling decision corresponding to the customer complaint user equipment 200 . For example, the customer complaint handling decision is "immediately dispatch workers to maintain base station 400".

值得說明的是，為了優化上述利用機器學習模型來決定客訴處理決策的準確性，機器學習模型訓練模組116可（預先）利用歷史客訴用戶設備訊號資料、歷史參考用戶設備訊號資料、歷史基地台資料、歷史參考基地台資料以及歷史客訴處理決策訓練所述至少一機器學習模型。換言之，機器學習模型訓練模組116可將歷史客訴用戶設備訊號資料、歷史參考用戶設備訊號資料、歷史基地台資料、歷史參考基地台資料以及歷史客訴處理決策設置為，用來訓練所述至少一機器學習模型的特徵。It is worth mentioning that in order to optimize the accuracy of the above-mentioned use of machine learning models to determine customer complaint handling decisions, the machine learning model training module 116 can (in advance) use historical customer complaint user equipment signal data, historical reference user equipment signal data, and historical Base station data, historical reference base station data and historical customer complaint handling decisions are used to train the at least one machine learning model. In other words, the machine learning model training module 116 can set the historical customer complaint user equipment signal data, historical reference user equipment signal data, historical base station data, historical reference base station data, and historical customer complaint processing decisions to train the above-mentioned Characteristics of at least one machine learning model.

綜上所述，本發明的決定用戶設備的客訴處理決策的電子裝置及方法可根據客訴用戶設備訊號資料、參考用戶設備訊號資料、基地台資料以及參考基地台資料以利用機器學習模型來決定出客訴處理決策。基此，行動網路的管理者在接收到特定用戶的客訴時，可有效率地針對此用戶決定出客訴處理決策。In summary, the electronic device and method for determining customer complaint handling decisions of user equipment according to the present invention can use machine learning models based on customer complaint user equipment signal data, reference user equipment signal data, base station data and reference base station data. Decide to handle customer complaints. Based on this, when a mobile network manager receives a customer complaint from a specific user, he or she can efficiently decide on a complaint handling decision for this user.

雖然本發明已以實施例揭露如上，然其並非用以限定本發明，任何所屬技術領域中具有通常知識者，在不脫離本發明的精神和範圍內，當可作些許的更動與潤飾，故本發明的保護範圍當視後附的申請專利範圍所界定者為準。Although the present invention has been disclosed above through embodiments, they are not intended to limit the present invention. Anyone with ordinary knowledge in the technical field may make some modifications and modifications without departing from the spirit and scope of the present invention. Therefore, The protection scope of the present invention shall be determined by the appended patent application scope.

100:決定用戶設備的客訴處理決策的電子裝置 110:儲存媒體 111:客訴用戶設備訊號資料接收模組 112:參考用戶設備訊號資料接收模組 113:基地台資料接收模組 114:參考基地台資料接收模組 115:客訴處理決策決定模組 116:機器學習模型訓練模組 120:收發器 130:處理器 200:客訴用戶設備 300a、300b:參考用戶設備 400:基地台 500a、500b:參考基地台 S201~S205:步驟 100: Electronic device that determines customer complaint handling decisions for user equipment 110:Storage media 111: Customer complaints about user equipment signal data receiving module 112: Reference user equipment signal data receiving module 113: Base station data receiving module 114: Reference base station data receiving module 115:Customer complaint handling decision-making module 116:Machine learning model training module 120: Transceiver 130: Processor 200: Customer complaint about user equipment 300a, 300b: Reference user equipment 400:Base station 500a, 500b: Reference base station S201~S205: steps

圖1是根據本發明的一實施例繪示的一種決定用戶設備的客訴處理決策的電子裝置的示意圖。 圖2是根據本發明的一實施例繪示的一種決定用戶設備的客訴處理決策的方法的流程圖。 FIG. 1 is a schematic diagram of an electronic device that determines customer complaint handling decisions for user equipment according to an embodiment of the present invention. FIG. 2 is a flow chart illustrating a method for determining customer complaint handling decisions for user equipment according to an embodiment of the present invention.

S201~S205:步驟 S201~S205: steps

Claims (9)

一種決定用戶設備的客訴處理決策的電子裝置，包括：儲存媒體，儲存多個模組；收發器，通訊連接至客訴用戶設備、參考用戶設備、基地台以及參考基地台；以及處理器，耦接所述儲存媒體以及所述收發器，並且存取和執行所述多個模組，其中所述多個模組包括：客訴用戶設備訊號資料接收模組，通過所述收發器接收對應於所述客訴用戶設備的客訴用戶設備訊號資料；參考用戶設備訊號資料接收模組，通過所述收發器接收對應於所述參考用戶設備的參考用戶設備訊號資料；基地台資料接收模組，通過所述收發器接收對應於所述基地台的基地台資料；參考基地台資料接收模組，通過所述收發器接收對應於所述參考基地台的參考基地台資料；以及客訴處理決策決定模組，將所述客訴用戶設備訊號資料、所述參考用戶設備訊號資料、所述基地台資料以及所述參考基地台資料輸入至至少一機器學習模型以決定對應於所述客訴用戶設備的客訴處理決策，其中所述客訴用戶設備通訊連接至所述基地台，且所述參考用戶設備通訊連接至所述基地台， 其中所述參考用戶設備與所述客訴用戶設備的距離小於預設門檻值。 An electronic device that determines customer complaint handling decisions of user equipment, including: a storage medium that stores multiple modules; a transceiver that is communicatively connected to customer complaint user equipment, reference user equipment, base stations, and reference base stations; and a processor, Couple the storage medium and the transceiver, and access and execute the plurality of modules, wherein the plurality of modules include: a customer equipment signal data receiving module, which receives the corresponding data through the transceiver. Customer complained user equipment signal data of the customer complained user equipment; a reference user equipment signal data receiving module, receiving the reference user equipment signal data corresponding to the reference user equipment through the transceiver; a base station data receiving module , receiving base station data corresponding to the base station through the transceiver; a reference base station data receiving module, receiving reference base station data corresponding to the reference base station through the transceiver; and customer complaint handling decisions A decision module that inputs the customer complaint user equipment signal data, the reference user equipment signal data, the base station data, and the reference base station data into at least one machine learning model to determine the response to the customer complaint user equipment signal data. Customer complaint handling decision of the equipment, wherein the customer complaint user equipment is communicatively connected to the base station, and the reference user equipment is communicatively connected to the base station, The distance between the reference user equipment and the customer user equipment is less than a preset threshold. 如請求項1所述的電子裝置，其中所述參考基地台與所述基地台的距離小於距離門檻值。 The electronic device according to claim 1, wherein the distance between the reference base station and the base station is less than a distance threshold. 如請求項1所述的電子裝置，其中所述客訴用戶設備訊號資料包括平均訊號強度、平均速率、最大速率以及最小速率。 The electronic device according to claim 1, wherein the customer user equipment signal data includes average signal strength, average rate, maximum rate and minimum rate. 如請求項1所述的電子裝置，其中所述參考用戶設備訊號資料包括平均訊號強度、訊號強度標準差、平均速率、速率標準差、平均最大速率、最大速率標準差、平均最小速率以及最小速率標準差。 The electronic device of claim 1, wherein the reference user equipment signal data includes average signal strength, signal strength standard deviation, average rate, rate standard deviation, average maximum rate, maximum rate standard deviation, average minimum rate, and minimum rate standard deviation. 如請求項1所述的電子裝置，其中所述基地台資料包括基地台告警訊息以及基地台障礙歷史紀錄。 The electronic device as claimed in claim 1, wherein the base station information includes base station alarm messages and base station obstruction history records. 如請求項1所述的電子裝置，其中所述參考基地台資料包括基地台告警訊息以及基地台障礙歷史紀錄。 The electronic device as claimed in claim 1, wherein the reference base station information includes base station alarm messages and base station obstruction history records. 如請求項1所述的電子裝置，其中所述至少一機器學習模型包括下列的至少其中之一：隨機森林模型、梯度提升樹模型以及神經網路模型。 The electronic device of claim 1, wherein the at least one machine learning model includes at least one of the following: a random forest model, a gradient boosting tree model, and a neural network model. 如請求項1所述的電子裝置，其中所述多個模組更包括機器學習模型訓練模組，其中所述機器學習模型訓練模組利用歷史客訴用戶設備訊號資料、歷史參考用戶設備訊號資料、歷史基地台資料、歷史參考基地台資料以及歷史客訴處理決策訓練所述至少一機器學習模型。 The electronic device of claim 1, wherein the plurality of modules further includes a machine learning model training module, wherein the machine learning model training module utilizes historical customer complaint user equipment signal data and historical reference user equipment signal data. , historical base station data, historical reference base station data and at least one machine learning model for historical customer complaint handling decision training. 一種決定用戶設備的客訴處理決策的方法，包括：接收對應於客訴用戶設備的客訴用戶設備訊號資料；接收對應於參考用戶設備的參考用戶設備訊號資料；接收對應於基地台的基地台資料；接收對應於參考基地台的參考基地台資料；以及將所述客訴用戶設備訊號資料、所述參考用戶設備訊號資料、所述基地台資料以及所述參考基地台資料輸入至至少一機器學習模型以決定對應於所述客訴用戶設備的客訴處理決策，其中所述客訴用戶設備通訊連接至所述基地台，且所述參考用戶設備通訊連接至所述基地台，其中所述參考用戶設備與所述客訴用戶設備的距離小於預設門檻值。 A method for determining customer complaint handling decisions for user equipment, including: receiving customer complaint user equipment signal data corresponding to the customer complaint user equipment; receiving reference user equipment signal data corresponding to the reference user equipment; receiving base station data corresponding to the base station data; receiving reference base station data corresponding to the reference base station; and inputting the customer user equipment signal data, the reference user equipment signal data, the base station data and the reference base station data to at least one machine Learning a model to determine a customer complaint handling decision corresponding to the customer complaint user equipment, wherein the customer complaint user equipment is communicatively connected to the base station, and the reference user equipment is communicatively connected to the base station, wherein the The distance between the reference user equipment and the customer user equipment is less than a preset threshold.
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