Time slice-based tariff dispute processing method, device, medium and product

Abstract

This application relates to the field of Internet television technology, and provides a method, device, medium, and product for handling tariff disputes based on time slices. The method includes: responding to a tariff dispute handling request, acquiring multi-source business event records associated with a target object, constructing a standard event sequence based on the multi-source business event records, and generating billing time slices based on time nodes in the standard event sequence; determining the billing receivable data under each billing time slice based on the billing strategy corresponding to each billing time slice; comparing the billing receivable data and billed data under each billing time slice to determine the billing difference and the cause of the billing difference; and determining the tariff dispute handling method based on the billing difference and the cause of the billing difference. The time-slice-based tariff dispute handling method provided by this application can effectively reduce verification costs and achieve interpretable accounting of billing differences.

Description

Technical Field

[0001] This application relates to the field of Internet television technology, and in particular to a method, device, medium and product for handling tariff disputes based on time-slice. Background Technology

[0002] In existing customer service and billing systems, when users initiate billing disputes, agents typically query user information, order records, bills, and playback logs through Customer Relationship Management (CRM) systems, Business Support Systems (BSS), and independent log platforms. Some systems display multi-source information on a single interface through integrated dashboards, but the source of the amount still relies on the backend billing black box results. The frontend cannot reconstruct the time slice of the user's status by event, nor can it independently recalculate the amount due. Other solutions introduce rule engines to perform pattern matching on events such as orders and changes, but this can only perform coarse-grained verification at the billing period level. When cross-day activation, trial deductions, or stacked discounts are involved, the formation process of each receivable cannot be explained. In addition, QoE quality alarms on the operations side mostly remain at the experience level, are not linked to billing recalculation, and lack end-to-end evidence solidification, making it difficult to reconstruct the basis for verification in review scenarios.

[0003] The common drawback of the above solutions is that when a user initiates a fee dispute, the existing system cannot start from the original business event and calculate the actual fee that the user should incur according to the business logic. Customer service needs to rely on black-box results to make manual inferences, which is costly to verify and lacks explanatory basis. Summary of the Invention

[0004] This application provides a time-slice-based method, device, medium, and product for handling tariff disputes, in order to solve the defects in the prior art where existing systems cannot calculate the actual charges that users should incur, causing customer service to rely on black-box results for manual inference, resulting in high verification costs and a lack of interpretive basis.

[0005] This application provides a time-slice-based method for handling tariff disputes, including the following steps: In response to a tariff dispute resolution request, the system acquires multi-source business event records associated with the target object and constructs a standard event sequence based on these records. Based on the time nodes in the standard event sequence, it generates billing time slices. Based on the billing strategy corresponding to each billing time slice, it determines the billing receivable data for that time slice. It compares the billing receivable data with the billed data for each time slice to determine the billing discrepancy and the cause of the discrepancy. Based on the billing discrepancy and the cause of the discrepancy, it determines the tariff dispute resolution method.

[0006] According to a method provided in this application, in response to a tariff dispute resolution request, multiple source business event records associated with a target object are obtained, and a standard event sequence is constructed based on the multiple source business event records. The method includes: in response to a tariff dispute resolution request, parsing the identification information of the target object carried in the tariff dispute resolution request; obtaining multiple original event records associated with the target object from multiple business systems based on the identification information; performing deduplication processing on the multiple original event records; and converting the deduplicated multiple original event records into standard events of a unified format to obtain a standard event sequence.

[0007] According to a method provided in this application, a billing time slice is generated based on time nodes in a standard event sequence, including: Billing time slices are generated using the billing period boundaries in the standard event sequence and the occurrence time of business change events as dividing points. Business change events include at least one of subscription events, change events, or cancellation events.

[0008] According to a method provided in this application, the billing strategy includes at least one of the following: package billing rules, fee conversion method, discount stacking rules, trial deduction rules, product mutual exclusion relationship, amount rounding rules, upper limit of billing amount, lower limit of billing amount, and automatic renewal enabled status.

[0009] According to a method provided in this application, a method for handling tariff disputes is determined based on the billing difference and the reason for the billing difference, including: The attribution of responsibility is determined based on the billing difference, the reason for the billing difference, and the preset liability determination rules; Based on the attribution of responsibility and the billing difference, a method for handling tariff disputes is generated.

[0010] According to a method provided in this application, the liability determination rules include platform-side determination conditions and user-side determination conditions. The platform-side determination conditions are used to limit the conditions under which liability is attributable to the platform, and the user-side determination conditions are used to limit the conditions under which liability is attributable to the user.

[0011] According to a method provided in this application, liability is determined based on the billing difference, the cause of the billing difference, and preset liability determination rules, including: Service quality events and network quality indicators are extracted from standard event sequences; quantitative correlation analysis with time window alignment is performed on service quality events and network quality indicators to obtain attribution analysis results; based on the attribution analysis results, billing discrepancies, the causes of billing discrepancies, and preset responsibility determination rules, the attribution of responsibility is determined.

[0012] According to a method provided in this application, service quality events include playback anomaly events, and network quality metrics include network latency, packet loss rate, and available bandwidth. A quantitative correlation analysis with time windows is performed on service quality events and network quality metrics to obtain attribution analysis results, including: Statistical analysis of playback anomaly events is performed according to preset time windows to obtain a playback anomaly ratio sequence within each preset time window. This playback anomaly ratio sequence characterizes the change over time of the ratio of the number of playback anomaly events to the total number of playback events within each preset time window. Statistical analysis of network latency, packet loss rate, and available bandwidth is also performed according to preset time windows to obtain a network quality indicator sequence within each preset time window. This network quality indicator sequence characterizes the change over time of the measured values ​​of network quality indicators within each preset time window. The correlation between the playback anomaly ratio sequence and the network quality indicator sequence is determined. The occurrence ratio of anomaly time windows in the playback anomaly ratio sequence is determined; the occurrence ratio of anomaly time windows is the ratio of the number of anomaly time windows to the total number of preset time windows. Based on the correlation and the occurrence ratio of anomaly time windows, the attribution analysis results are determined.

[0013] According to a method provided in this application, the above method further includes: The data involved in this tariff dispute resolution process is solidified to generate evidence records; signature information is generated for the evidence records; and the signature information is stored in association with the evidence records.

[0014] According to a method provided in this application, the above method further includes: Based on the tariff dispute handling method, the target work order is generated or associated in the work order system.

[0015] According to a method provided in this application, the above method further includes: Determine and record the real-time processing status of the target work order.

[0016] According to a method provided in this application, the above method further includes: The interface displays the session information and dispute resolution method for the tariff dispute resolution request; in response to the operation instructions for the dispute resolution method, the tariff dispute resolution method is executed.

[0017] This application also provides a time-slice-based tariff dispute resolution device, including the following modules: The acquisition module is used to respond to tariff dispute handling requests, acquire multi-source business event records associated with the target object, and construct a standard event sequence based on the multi-source business event records.

[0018] The generation module is used to generate billing time slices based on time nodes in a standard event sequence.

[0019] The first determination module is used to determine the billing receivable data under each billing time slice based on the billing strategy corresponding to each billing time slice.

[0020] The second determination module is used to compare the billing receivable data and the billed data under each billing time segment to determine the billing difference and the reason for the billing difference.

[0021] The third determination module is used to determine the method for handling tariff disputes based on the billing difference and the reason for the billing difference.

[0022] This application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the time-slice-based tariff dispute resolution method as described above.

[0023] This application also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the time-slice-based tariff dispute resolution method as described above.

[0024] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the time-slice-based tariff dispute resolution method as described above.

[0025] The time-slice-based billing dispute resolution method provided in this application first acquires multi-source business event records associated with the target object and constructs a standard event sequence. Based on this, it automatically segments billing time slices according to the time nodes within the events. Since the business status and billing strategy within each time slice are uniquely determined, the solution can independently calculate the receivable data for that segment based on the original events without calling the black-box interface of the backend billing system. By comparing the receivable data for each billing time slice with the billed data segment by segment, not only can the accurate billing difference be obtained, but the difference can also be directly attributed to the specific business event or time slice that generated the difference, thereby automatically outputting the reason for the difference (e.g., "X yuan was overcharged due to the trial deduction not taking effect within a certain time slice"). Finally, the billing dispute resolution method is automatically mapped based on the difference and its reason. Therefore, in this application, when a user initiates a billing dispute, the actual cost incurred by the user can be calculated segment by segment, eliminating the need for customer service personnel to perform manual inference, thus effectively reducing verification costs and achieving interpretable calculation of billing differences. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a flowchart illustrating a time-slice-based tariff dispute resolution method provided in this application.

[0028] Figure 2 This is a schematic diagram of a time-slice-based tariff dispute resolution device provided in this application.

[0029] Figure 3 This is a schematic diagram of the structure of an electronic device provided in this application. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0031] The following is combined Figures 1 to 3 This application describes the time-slice-based tariff dispute resolution method provided.

[0032] Figure 1 This is a flowchart illustrating a time-slice-based tariff dispute resolution method provided in this application, applicable to electronic devices (e.g., servers or customer service systems deployed with the time-slice-based tariff dispute resolution method provided in this application). Figure 1 As shown, the method includes the following steps S101-S105.

[0033] S101, in response to a tariff dispute resolution request, obtain multi-source business event records associated with the target object, and construct a standard event sequence based on the multi-source business event records.

[0034] Multi-source business event records refer to raw event records obtained from multiple different business systems. These business systems may include, but are not limited to, multiple systems such as order systems, billing systems, authentication systems, playback systems, terminal systems, broadband systems, and customer service systems.

[0035] In this embodiment of the application, when a user initiates an inquiry or complaint via telephone or online customer service regarding tariff issues for a certain billing period (hereinafter referred to as the target billing period), a tariff dispute resolution request is triggered. Thus, the electronic device can receive and respond to this tariff dispute resolution request.

[0036] The target billing period can be any billing cycle, for example, a calendar month (from the 1st of each month to the end of the month).

[0037] In one example, after receiving a tariff dispute resolution request, the electronic device can obtain multi-source business event records associated with the target object through the following steps A-D, and construct a standard event sequence.

[0038] Step A: In response to the tariff dispute resolution request, parse the identification information of the target object carried in the tariff dispute resolution request.

[0039] The identification information (hereinafter referred to as identification information A) carried in the tariff dispute resolution request can be the caller's number or the online session identifier. This application embodiment does not specifically limit the identification information A.

[0040] Specifically, after receiving a tariff dispute resolution request, the electronic device can parse the tariff dispute resolution request to obtain identification information A.

[0041] Step B: Based on the identification information, retrieve multiple original event records associated with the target object from multiple business systems.

[0042] In one example, an electronic device can determine the user identifier (UID) and device identifier (DID) of a target object based on identification information A. The electronic device can then use the target object's UID and DID, along with the time range of the target billing period (or target billing cycle), as input to read multiple raw event records associated with the target object from each business system within the target billing period.

[0043] First, the process of determining the UID and DID of a target object based on the identification information A of an electronic device is described.

[0044] After obtaining identification information A, the electronic device can retrieve various identity identifiers (hereinafter referred to as identification information B) associated with the tariff dispute resolution request from the identifier set based on identification information A, thereby enriching the identification basis of the target object. In one example, the identifier set may include, but is not limited to: mobile phone number, IPTV account, broadband account, set-top box serial number, contract number, etc.

[0045] The Customer Relationship Management (CRM) system pre-maintains a primary key relationship table and an account binding table, storing the correspondence between identifier information B, UID, and DID. Thus, after an electronic device obtains identifier information B, it can use B as input to match it in the CRM's primary key relationship table and account binding table. If a candidate record is found, the electronic device can use the UID and DID contained in that candidate record as the UID and DID of the target object.

[0046] When multiple candidate records are matched, the electronic device can determine the matching score of each candidate record according to the preset evaluation index, and use the UID and DID contained in the candidate record with the highest score as the UID and DID of the target object.

[0047] Preset evaluation indicators may include, but are not limited to: whether the most recent authentication was successful, whether the installation address is consistent, and whether the usage records in a recent period of time come from the same device.

[0048] In one example, the electronic device can determine the matching score for each candidate record using the following formula. .

[0049] in, This represents the freshness score of the most recent authentication, with a value ranging from 0 to 1. This represents the time interval between the current time and the most recent successful authentication. For the preset time threshold, The preset time decay coefficient, The parentheses (·) represent an indicator function. The function evaluates to 1 if the condition within the parentheses is true, and 0 otherwise. As can be seen from the formula above, the shorter the time since the most recent successful authentication, the better. The closer the score is to 1, the fresher the authentication status corresponding to the candidate record is, and the higher its credibility.

[0050] This indicates whether the installation address matches. If the installation address in the candidate record matches the address information associated with this tariff dispute resolution request, then... The value is 1 if it is not 1, otherwise the value is 0.

[0051] This indicates the percentage of recent usage records from the same device. This represents the total number of recent usage records. This represents the number of recent usage records originating from the same device.

[0052] , , Corresponding to , , The weighting coefficients for the three evaluation metrics. The specific values ​​of each weighting coefficient can be configured according to the needs of the actual business scenario, for example, based on experience in determining the importance of each metric in identity matching.

[0053] In one example, while determining the UID and DID of the target object, the electronic device can also generate a unique session number for this tariff dispute resolution session. This session number can be used to identify the current tariff dispute resolution session, so as to associate the data and results generated in each processing stage subsequently.

[0054] In one example, if a unique candidate record cannot be determined based on the above matching score calculation process (e.g., multiple candidate records have the same matching score and are all the highest score, or all candidate records have matching scores lower than a preset minimum confidence threshold), the electronic device can mark this tariff dispute processing session as "information pending". In this state, the electronic device will only perform the most basic data retrieval operation in subsequent steps, and will continue the subsequent processing flow after the relevant information is fully supplemented.

[0055] After determining the UID and DID of the target object using the above method, the electronic device can input the UID and DID of the target object, as well as the time range of the target billing period, into each business system and read the multiple original event records associated with the target object within the target billing period recorded in each business system.

[0056] In one example, the raw event records read by the electronic device from various business systems can be incremental data. Specifically, the electronic device can simultaneously read the timestamp or auto-incrementing sequence number of the last record of each business system (such as the last billing period or the last accounting cycle), and based on the timestamp or auto-incrementing sequence number, obtain the raw event records within the corresponding incremental range from the corresponding business system by initiating an interface call or reading incremental logs.

[0057] Step C involves deduplicating multiple original event records.

[0058] In one example, the electronic device can generate a record summary value for each original event record, which uniquely identifies the original event record. The electronic device can then deduplicate multiple original event records based on this record summary value and the batch number of the current acquisition.

[0059] The batch number refers to the number of the original event records collected in this batch.

[0060] In one example, the electronic device can use a hash algorithm to generate a record digest value corresponding to each original event record, calculated as follows: Where sys is the business system identifier, ts is the timestamp or auto-incrementing sequence number corresponding to the original event record, uid is the user identifier, and payload is the content of key business fields used for deduplication concatenated in a fixed order.

[0061] After determining the record summary value corresponding to each original event record using the above method, the electronic device can perform deduplication on original event records with the same batch number (i.e., the same batch) and the same record summary value, retaining only one valid record. When performing deduplication across batches, using the batch number + record summary value H as the combined deduplication key can avoid accidentally deleting legitimate records with the same summary value from different batches, ensuring the accuracy of deduplication.

[0062] It should be noted that for original event records with abnormal timestamps or missing key fields, electronic devices can add annotations to indicate the abnormalities without modifying the original record content, thus preserving the originality of the data.

[0063] Step D involves converting the multiple original event records after deduplication into standard events in a unified format to obtain a standard event sequence.

[0064] Standard events may include, but are not limited to: event type, occurrence time, business system, primary key (UID or DID), attribute set, and storage location of original evidence. Time attributes may include, but are not limited to, fields such as product code, package policy number, billing period number, failure code meaning, and device model. Time attributes can be obtained from a pre-defined mapping table in the electronic device. Event types may include, but are not limited to: order events, cancellation events, package change events, billing events, authentication success or failure events, playback anomaly events, device offline / remote events, link quality anomaly events, and effective date adjustment events, among others.

[0065] In one example, an electronic device may be equipped with a preset event model. After obtaining multiple original event records after deduplication, the electronic device can input each original event record into the preset event model to obtain the standard event corresponding to each original event record, thereby obtaining a standard event sequence.

[0066] In one example, during the generation of standard events, electronic devices can fill in missing fields with default values ​​according to preset rules and indicate the reasons for the missing fields, ensuring that the event structure is complete and traceable.

[0067] S102 generates billing time slices based on time nodes in the standard event sequence.

[0068] In one example, electronic devices can generate billing time slices using the billing period boundaries in a standard event sequence and the occurrence time of business change events as dividing points.

[0069] Among them, business change events may include, but are not limited to, at least one of ordering events, change events, or cancellation events.

[0070] Each billing time slice does not overlap with another.

[0071] Specifically, electronic devices can sort the standard events in the standard event sequence according to time order, and then use the billing period boundary and the occurrence time of business change events as the dividing points to generate continuous and non-overlapping billing time slices.

[0072] The set of split points can be obtained by merging and deduplicating the occurrence times of billing cycle boundaries and business change events, and then sorting them chronologically. In one example, the set of split points can be denoted as: B = {b...} 0， b1, ..., b M The k-th billing time slice can be denoted as a slice. k =[b k b k+1 ).

[0073] S103, Based on the billing strategy corresponding to each billing time slice, determine the billing receivable data under that billing time slice.

[0074] Billing policies are used to characterize the combination of billing rules that are in effect within a billing time slice.

[0075] In one example, the billing strategy may include, but is not limited to, at least one of the following: package billing rules (such as package unit price), fee conversion method, discount rules, discount stacking rules, trial deduction rules, product mutual exclusion relationship, amount rounding rules, upper limit of billing amount, lower limit of billing amount, and automatic renewal enabled status.

[0076] In one example, before executing S103, the electronic device can also generate a billing status table corresponding to each billing time slice, and the billing status table corresponding to each billing time slice can store the billing policy corresponding to each billing time slice.

[0077] Specifically, after the electronic device generates a billing time slice, it can establish a billing status table for each billing time slice and update the billing status table corresponding to each billing time slice according to the order of each billing time slice and based on the billing strategy included in each billing time slice.

[0078] The billing strategy included in each billing time slice refers to the billing strategy corresponding to each standard event located within that billing time slice.

[0079] Specifically, the electronic device can first sort the standard events in the standard event sequence according to time order. For multiple standard events occurring at the same time, the electronic device can sort them according to the preset priority of the business system and the priority of the event type. Then, the electronic device can process each billing time slice... k A revision number (rev) is set, starting from the initial state, i.e., rev=0. For each billing time slice, the electronic device can process the sorted standard events within that billing time slice sequentially. After parsing and processing each standard event within that billing time slice, the electronic device can generate a state snapshot states[k,rev+1] and update the billing policy contained in that standard event in the billing state table corresponding to that billing time slice.

[0080] The fields in the billing status table may include, but are not limited to, the package billing rule field (price). P ), cost conversion method field (proration) mode ), discount rule field (discount) pct_set ), Discount stacking rules field (discount) amount_set ), trial deduction rules field (trial) deduction ), product mutual exclusion field (mutex) group ), rounding rules field rule_rho ), Billing Amount Limit Field (C) min ), Billing Amount Limit Field (C) max At least one of the following:

[0081] In one example, the event types, sorted by priority from highest to lowest, could be: effective date adjustment event, order event, package change event, cancellation event, and billing event.

[0082] In one example, the electronic device can also write the differences before and after the change of fields in the billing status table corresponding to each billing time slice into the change log.

[0083] After obtaining the billing status table corresponding to each billing time slice through the above method, when the electronic device executes S103, it can obtain the billing strategy corresponding to the billing time slice from the billing status table corresponding to each billing time slice, and determine the billing receivable data under the billing time slice based on each billing strategy under the billing time slice.

[0084] In one example, for each billing time slice, if there is a conflict in the billing policy corresponding to that billing time slice, the electronic device can determine the billing receivable data under the billing time slice according to the preset priority and execution order.

[0085] A billing policy conflict occurs when, within a billing time slice, there are multiple billing policies that cannot be effective simultaneously (i.e., mutually exclusive), or multiple billing policies whose effective order is uncertain.

[0086] The preset priority is used to determine the execution strategy for conflicting billing policies of the same type. For example, if the billing policy corresponding to the same billing time slice contains multiple discount rules that cannot be effective simultaneously, the preset priority can be used to determine which discount rule to use for billing.

[0087] The preset execution order refers to the execution order of different billing strategies. In one example, the preset execution order can be: first billing according to the fee conversion method, then billing according to the discount rules, then billing according to the discount stacking rules and trial deduction rules, and finally billing according to the amount rounding rules, the upper limit of the billing amount, and the lower limit of the billing amount.

[0088] In one example, for each billing time slice, after retrieving the corresponding billing policy from the billing status table, the electronic device can determine whether there is a conflict between the billing policies for that time slice. If there is no conflict, the electronic device can directly determine the billing receivable data for that time slice. If there is a conflict, the electronic device can retain the highest-priority billing policy among the conflicting policies according to a preset priority. Then, the electronic device can first determine the basic fee by referring to the first formula below. Then, refer to the second formula below to determine the cost after applying the discount and preferential policies for that billing time slice. Then, the electronic device can refer to the third formula below to determine the billing receivable data for that billing time slice. .

[0089] in, Let be the number of days in the k-th billing time slice, D be the total number of days in the target billing period, P be the unit price of the service subscribed by the user in this billing time slice, which can be obtained from the billing status table, and R be the set of discount rules. Let A be the i-th discount rule, and A be the set of discount stacking rules. This is the rule for stacking the j-th discount. The trial deduction amount is the trial deduction limit for the k-th billing time slice; This represents the lower limit of the billing amount for the corresponding billing time segment. This represents the maximum billing amount for the corresponding billing time slice. The rules for determining the values ​​of billing receivables, such as rounding to the nearest integer, rounding to the nearest whole number, or retaining two decimal places, can be obtained from the billing status table.

[0090] In one example, after calculation When the value is less than 0, the electronic device can display the billing and receivable data for the billing time slice. The value is set to 0, and a deduction record (credit) is generated. k And credit k = Used for bookkeeping or subsequent cross-segment deductions.

[0091] In one example, if the billing status table for a certain billing time slice is missing a service unit price (P), the electronic device can use the same plan version from the previous billing time slice. version The corresponding service unit price. If there is no service unit price for the same package version in the previous billing time slice, the electronic device can mark the billing time slice as unbilled, output the information to be supplemented, and record the reason for unbilled: service unit price missing (price). missing ).

[0092] In one example, electronic devices can be activated via a clamp. from The field records the values ​​of the billing receivable data under the billing time slice before being constrained by the upper and lower limits of the billing amount, and is recorded using a clamp. to The field records the billing receivable data under the billing time slice after being constrained by the upper and lower limits of the billing amount, which facilitates subsequent review and traceability.

[0093] In one example, when updating the billing status table corresponding to each billing time slice, the aforementioned electronic device can also record the various billing policies involved in each billing time slice and the execution strategy of each billing policy. Specifically, this can be achieved through a rule-based ordered list. hit_seq Recording implementation: Before each calculation, the list is cleared, and then records are written sequentially according to the priority of each billing strategy. Each record can contain the rule number of the corresponding billing strategy. id Priority, version number, and apply time. ts If there are conflicts between similar billing policies, the one with higher priority will take effect.

[0094] S104 compares the billing receivable data and billed data for each billing time segment to determine the billing difference and the reason for the billing difference.

[0095] The billing data includes the billing details that the billing system actually generates and pushes to the bill for the target object within the target billing period. In one example, the billing data may include, but is not limited to: billing period identifier, product code, billing item name, billing amount, billing time, bill detail number, etc.

[0096] In one example, after obtaining the billing receivable data for each billing time slice via S103, the electronic device can determine the user's billing receivable data for the target billing period based on the billing receivable data for each billing time slice using the following formula.

[0097] Where K represents the number of billing time slices under the target billing period.

[0098] Afterwards, the electronic device can compare the billing receivable data for the target billing period with the billing data already stored in the billing system item by item to determine the billing difference and the reason for the billing difference.

[0099] In one example, the electronic device can also generate a comparison table (also known as a combined list) of billing receivable data and billed data, and the comparison table may include the target billing period, each billing time slice in the target billing period, the product identifier of the product ordered by the user, and the billing receivable data and billed data corresponding to each service under each billing time slice.

[0100] In one example, the electronic device may also generate a difference table, which may include a target billing period, each billing time slice in the target billing period, the service identifier of the service subscribed by the user, the billing receivable data and billed data corresponding to each service under each billing time slice, and the billing difference for each service under each billing time slice.

[0101] In one example, the billing difference for electronic devices can be determined as follows: For each corresponding product in the billing receivables and billed receivables data for the target billing period, the difference between the receivable amount in the billing receivables data and the actual amount received in the billed receivables data for the target billing period is calculated. The formula for calculating the billing difference Delta can be expressed as: in, This indicates the actual amount received for a specific product in the billing data. This indicates the amount of receivable for this product in the billing receivables data under the target billing period.

[0102] If Delta is greater than 0, it indicates that the billing system has overcharged, i.e., there is an overcharge difference, denoted as Delta. plus=Delta. If Delta is less than 0, it means the billing system has undercharged. plus = 0 indicates that the amount receivable is consistent with the amount actually received, and there is no billing difference.

[0103] After determining the billing difference, the electronic device further performs attribution analysis on each billing difference to determine the cause of the billing difference.

[0104] The reasons for billing discrepancies may include, but are not limited to, duplicate charges, offset effective date, failure to execute trial credit, incorrect stacking of discounts, conflicting mutually exclusive products, and differences in rounding rules, among other things.

[0105] Duplicate billing refers to a situation where, within the same billing period, multiple billing details exist for the same product in the billing data, while the billing receivable data for the target billing period shows only one billing receivable. Electronic devices can detect duplicate billing by comparing the billing data in the billing data in the billing data in the target billing period. If the same product is found to appear repeatedly in the billing data, and the billing receivable data for the target billing period shows only one billing receivable, the electronic device can mark the reason for the billing difference as "duplicate billing."

[0106] Effective date offset refers to a discrepancy between the actual execution date of an order, package change, or cancellation event and the effective date stipulated in the billing strategy. Trial discount not executed: The target customer enjoys trial discount rights during the target billing period, but the billing system fails to execute the discount correctly upon billing. Incorrect discount stacking: When multiple discount strategies (such as discount rules or discount stacking rules) are in effect simultaneously, the billing system's execution of stacking or mutual exclusion processing does not conform to the preset priority and execution order. Mutually exclusive product conflict: The target customer simultaneously orders multiple mutually exclusive products, and the billing system's billing processing of mutually exclusive products does not conform to the preset product mutual exclusion relationship. Rounding rule difference: The rounding rules used during accounts receivable recalculation are inconsistent with the rounding rules actually used by the billing system, resulting in a slight difference in the final amount.

[0107] In one example, if an electronic device marks a billing time slice as "unbilled" in S103 and records the reason for unbilled status (such as missing service price), then in S104, the electronic device can mark the reason for the billing difference corresponding to the billing time slice as "missing billing basis" and use the unbilled reason recorded in S103 as a supplementary explanation.

[0108] In one example, the electronic device can also perform quantitative attribution analysis on billing discrepancies, that is, determine the contribution amount of each cause to the billing discrepancy. For example, if there are multiple causes for discrepancies in the same product item, the electronic device can allocate the discrepancy amount to each cause item according to a preset attribution priority, or label it as being caused by multiple causes.

[0109] In one example, the electronic device can also determine whether the billing receivable data is subject to the billing amount cap (C) based on the clampfrom and clampto fields recorded in the billing status table. max ) or minimum billing amount (C min The truncation occurs due to constraints. If truncation exists, the electronic device can record the truncation information as supplementary information for the billing difference in the difference list.

[0110] Through the above process, the electronic device ultimately generates a difference list containing billing differences and classifications of the reasons for these differences. Each record in the difference list may include, but is not limited to, the following information: product identifier, amount receivable, amount received, billing difference value, difference reason classification, relevant billing time slice range, associated rule record, and supplementary information.

[0111] This list of differences will serve as an important basis for determining the method for handling tariff disputes in subsequent S105.

[0112] In one example, a user can subscribe to multiple products (also referred to as product items). Accordingly, the billing receivables for each billing time slice can include the billing receivables for each product within that billing time slice. For instance, assuming the user's subscribed products include broadband and IPTV, the billing receivables for each billing time slice can include the broadband fee and IPTV fee for that specific billing time slice.

[0113] S105, Based on the billing difference and the reason for the billing difference, determine the method for handling tariff disputes.

[0114] After obtaining a list of differences, including the billing difference and the reasons for the billing difference, through S104, the electronic device further determines the handling plan for this tariff dispute based on the list of differences, namely the tariff dispute handling method.

[0115] In one example, S105 may include steps E to F below.

[0116] Step E: Determine the attribution of responsibility based on the billing difference, the reason for the billing difference, and the preset liability determination rules.

[0117] Attribution of responsibility is used to characterize which party should bear the responsibility for the billing discrepancy. In one example, attribution of responsibility may include platform-side responsibility and user-side responsibility.

[0118] Pre-defined liability determination rules are used to provide a basis for determining liability attribution. In one example, the liability determination rules may include platform-side determination conditions and user-side determination conditions. Platform-side determination conditions are used to define the conditions that must be met to determine liability attribution to the platform; user-side determination conditions are used to define the conditions that must be met to determine liability attribution to the user.

[0119] In one example, the platform-side judgment criteria may include at least one of the following: the recalculation rule path (i.e., the method for determining the billing receivable data for the target billing period) is inconsistent with the billing system execution path (i.e., the method for the billing system to determine the billed data); duplicate billing for the same product in the same billing period; the deviation between the actual execution date of the business change and the effective date of the policy exceeds the preset tolerance; mutually exclusive products are effective at the same time; trial deduction is not executed; discount stacking is incorrect; service quality anomalies and network quality fluctuations are significantly correlated and there are alarms on the network side, etc.

[0120] The inconsistency between the recalculation rule path and the billing system execution path refers to the fact that the electronic device records the ordered list of rules in S103. hit_seq The execution strategy of the billing policy reflected in the billing system differs from the execution strategy of the billing system when actually issuing bills. For example, for the same discount scenario, the ordered list of rules retains discount rule A according to the preset priority, while the billing system actually executes discount rule B.

[0121] Duplicate billing for the same product in the same billing period refers to the following: In S104, the electronic device detects that there are multiple billing details for the same product in the billing data, but the billing receivable data under the target billing period shows that only one billing receivable should be generated. In other words, the reason for the difference is marked as "duplicate deduction".

[0122] The deviation between the actual execution date of a business change and the effective date of the policy exceeds the preset tolerance means that the deviation between the actual execution date of an order event, package change event, or cancellation event and the effective date stipulated in the billing policy exceeds the preset time tolerance threshold (e.g., more than 1 day). In this case, the reason for the difference is marked as "effective date offset".

[0123] The simultaneous activation of mutually exclusive products refers to the following: the target object simultaneously orders multiple products that have a mutual exclusion relationship, and these mutually exclusive products are simultaneously in an active state within the same billing time slice. This does not match the product mutual exclusion relationship field recorded in the billing status table in S103, and the reason for the difference is marked as "mutually exclusive product conflict".

[0124] "Trial deduction not executed" means that the target object is entitled to trial deduction during the target billing period, but the billing system does not execute the deduction correctly when issuing the bill, that is, the reason for the difference is marked as "trial deduction not executed".

[0125] An error in stacking discounts refers to a situation where, when multiple discount policies (such as discount rules or discount stacking rules) are in effect simultaneously, the billing system's execution of stacking or mutual exclusion processing does not conform to the preset priority and execution order. In other words, the reason for the discrepancy is marked as "discount stacking error".

[0126] A significant correlation between service quality anomalies and network quality fluctuations, coupled with network-side alerts, refers to the following: within the time period covered by the discrepancy list, the strength of the relationship obtained from attribution analysis is [value missing]. Greater than or equal to the preset correlation threshold And the proportion of abnormal time windows Greater than or equal to the preset recurrence threshold Meanwhile, the network-side SLA logs show corresponding alarm records on the local network or platform side.

[0127] In one example, the user-side determination criteria may include at least one of the following: the user's service is suspended due to unpaid fees, the user replaces the device without completing the binding, or the user continues to use the service after voluntarily unsubscribing.

[0128] User service suspension due to unpaid bills refers to the suspension of service for a target user due to unpaid bills during the target billing period, resulting in abnormal billing or service usage.

[0129] The user's failure to complete the binding after changing the device refers to the target user changing the terminal device (e.g., changing the set-top box) but failing to complete the binding operation between the new device and the account in the system, resulting in authentication failure or abnormal service usage records.

[0130] Continuing to use services after a user has voluntarily unsubscribed refers to situations where the target user has initiated an unsubscription process but continues to use the related services after the unsubscription takes effect, resulting in disputes over fees.

[0131] In one example, the electronic device can determine responsibility according to the following logic: when at least one of the platform-side determination conditions is met, but not all of the user-side determination conditions are met, the electronic device determines that the responsibility belongs to the platform side; when at least one of the user-side determination conditions is met, the electronic device determines that the responsibility belongs to the user side.

[0132] For example, an electronic device can automatically determine liability and assign a value to the liability indicator L according to the following logic: Where I(·) is an indicator function, which takes the value 1 when the condition inside the parentheses is true, and takes the value 0 otherwise. This indicates that none of the user-side judgment conditions are met. This indicates that the recalculation rule path and the billing system execution path are inconsistent. This indicates that the same product is billed repeatedly within the same payment period. This indicates that the deviation between the actual execution date of the business change and the effective date of the policy exceeds the preset tolerance. This indicates that mutually exclusive products are active simultaneously. This indicates that the trial discount was not applied or the discount was incorrectly applied. This indicates a significant correlation between service quality anomalies and network quality fluctuations, and that an alarm exists on the network side. Specifically, when at least one platform-side judgment condition is met, but not all user-side judgment conditions are met, L is 1, indicating that the responsibility lies with the platform side; when at least one user-side judgment condition is met, L is 0, indicating that the responsibility lies with the user side.

[0133] In one example, when determining responsibility for electronic devices, attribution analysis results can be further incorporated for a comprehensive assessment. Attribution analysis results characterize the correlation between service quality events and network quality indicators, helping to determine whether billing discrepancies are related to network quality or terminal issues.

[0134] Specifically, the electronic device can extract quality of service (QoS) events and network quality metrics from the standard event sequence generated by S101. In one example, QoS events may include playback anomaly events. Network quality metrics may include network latency, packet loss rate, and available bandwidth.

[0135] Subsequently, electronic devices can perform time-window aligned quantitative correlation analysis on the extracted service quality events and network quality metrics to obtain attribution analysis results. The specific process of quantitative correlation analysis may include: First, the electronic device can statistically analyze playback anomaly events according to preset time windows, obtaining a playback anomaly ratio sequence within each preset time window. The playback anomaly ratio sequence characterizes the change over time of the ratio of the number of playback anomaly events to the total number of playback events within each preset time window. In one example, the playback anomaly ratio within the i-th preset time window... It can be represented as: .in, This represents the number of playback errors that occur within this time window (such as the sum of the number of playback failure events and the number of records that trigger retries). This represents the total number of playbacks within that time window, i.e., the total number of playback start events.

[0136] Secondly, the electronic devices statistically analyze network latency, packet loss rate, and available bandwidth within the same preset time window, obtaining a network quality indicator sequence for each preset time window. The network quality indicator sequence characterizes the change in the measured statistical value of the corresponding network quality indicator over time within each preset time window. In one example, the network latency sequence lat(i) can be the average latency value within the time window, the packet loss rate sequence loss(i) can be the average packet loss rate within the time window, and the available bandwidth sequence bw(i) can be the average available bandwidth within the time window.

[0137] Next, the electronic device determines the correlation between the playback anomaly rate sequence and the network quality indicator sequence. In one example, the electronic device measures the linear correlation between the playback anomaly rate sequence and each network quality indicator sequence within the observation interval by calculating the Pearson correlation coefficient corr(·,·), and then weights them using preset weights a, b, and c to obtain a score indicating the strength of the relationship. Relationship strength score The calculation formula can be expressed as: Here, f(x) is a mapping function used to map the correlation combination result to the interval between 0 and 1. The weights a, b, and c are configured based on business experience and are used to balance the impact of latency, packet loss, and bandwidth. This represents a sequence of playback anomalies calculated over a fixed time window. This represents the network latency sequence statistically analyzed within the same time window, in milliseconds, and is calculated as the average value within that window. This represents the sequence of packet loss rates calculated within the same time window, with the average value taken within that window. This represents the available bandwidth sequence statistically analyzed within the same time window, with the average value taken within that window.

[0138] Simultaneously, the electronic device determines the proportion of abnormal time windows appearing in the abnormal playback ratio sequence. The abnormal time window refers to the proportion of abnormal playback ratios reaching a preset abnormal threshold. The preset time window. The proportion of abnormal time windows. This refers to the number of abnormal time windows. The ratio of the number of preset time windows to N, i.e. = / N.

[0139] Finally, electronic devices can determine the attribution analysis results based on the aforementioned correlations and the proportion of occurrences within anomalous time windows. In one example, when... ≥ At that time, electronic devices can determine that the relationship between playback abnormalities and network quality fluctuations is strongly correlated; when ≥ When the electronic device determines that the playback anomaly is recurring, and both of the above conditions are met simultaneously, the electronic device's attribution analysis results support the platform-side responsibility determination, that is, there is a significant correlation between the service quality anomaly and network quality fluctuations, and the anomaly is persistent, making it more likely to be attributed to platform-side or network-side issues.

[0140] , , All of these are configurable threshold parameters.

[0141] In one example, the threshold and The initial value can be determined jointly by historical data estimation and on-site target control. After going online, the electronic equipment can adaptively adjust the threshold on a daily or weekly basis: estimating the current positive judgment rate based on the manual review results of the most recent period. and in accordance with Update, among which To learn step length, For the target positive rate, the clip(·) function is used to limit the updated threshold within a safe range. , ]Inside; Similarly, updates are performed. To adapt to regional and device differences, thresholds can be maintained independently by region and terminal model. When the sample size of a certain bucket is insufficient, it will automatically fall back to the global threshold. All threshold and weight adjustments are recorded in the configuration change log, and the effective time and version number are included in the evidence object to ensure that the same session can be replayed to obtain consistent attribution analysis results.

[0142] After obtaining the attribution analysis results, the electronic device, based on the attribution analysis results, the billing difference, the cause of the billing difference, and the preset liability determination rules, jointly determines the attribution of liability and the corresponding liability indicator L.

[0143] Step F: Based on the attribution of responsibility and the billing difference, generate a method for handling tariff disputes.

[0144] After determining the attribution of responsibility, the electronic device calculates the suggested refund boundary based on the attribution of responsibility and the billing difference, and generates a handling plan for this billing dispute, namely the billing dispute handling method.

[0145] In one example, the electronic device first determines the value of the responsibility flag L based on the attribution of responsibility. When the responsibility is attributable to the platform, L is set to 1; when the responsibility is attributable to the user, L is set to 0.

[0146] Next, the electronic device calculates the overcharged difference, Delta. plus The difference (Delta) is collected in excess. plusThis refers to the portion of the amount already disbursed that exceeds the amount receivable. The calculation formula for this portion can be expressed as: Where C_billed is the amount already billed, and C_due is the billing receivable data for the target billing period obtained in S103.

[0147] Then, the electronic device is based on the difference in charges. Based on the liability indicator L and preset constraints, calculate the suggested refund amount. In one example, the suggested refund amount The calculation formula can be expressed as: in, This is the preset maximum billing amount; The influence level is determined based on the attribution analysis results; g(ell) is the proportional coefficient corresponding to the influence level; The base amount for this product during the target payment period can be the monthly price or the maximum receivable for that period. The above calculation results must include the supporting fields and the location of the original data involved for subsequent review and traceability.

[0148] In one example, the method for handling tariff disputes may include at least one of the following: a suggested refund amount, relationship repair steps, and a type of experience compensation. The suggested refund amount is the amount calculated above. .

[0149] The relationship repair step refers to the sequence of operations generated to repair subscription relationship anomalies based on the binding relationships and mutual exclusion configurations between the target object's user identifier, device identifier, and products. In one example, before generating the relationship repair step, the electronic device can first perform a subscription relationship consistency check. Specifically, the electronic device uses the target object's user-family member relationships, primary and secondary card relationships, device-account binding relationships, service mutual exclusion configurations, and overdue payment status as input to construct a user-device-product relationship table, checking for issues such as duplicate subscriptions, simultaneous activation of mutually exclusive products, and incorrect device binding. The electronic device can quantify the degree of conflict by calculating the relationship conflict degree S_conf, which can be expressed by the following formula: Where G is the set of mutually exclusive groups; This indicates whether the g-th mutual exclusion group has active products simultaneously; if yes, it is set to 1, otherwise it is set to 0. This indicates whether there is a mis-bound device or account; return 1 if yes, otherwise return 0. This indicates whether there is a duplicate order; return 1 if yes, otherwise return 0.

[0150] Based on the relationship check results, the electronic device generates a repair sequence according to the configured mutual exclusion relationship table. In one example, the relationship repair steps may include at least one of the following: clearing outstanding fees and reordering, unbinding the old device and binding the new device, and eliminating mutual exclusion product conflicts. If necessary, the electronic device may trigger a brief review after performing the repair to confirm whether the problem has been resolved.

[0151] Experience compensation type refers to the non-cash compensation method provided to the target audience based on the results of attribution analysis. In one example, experience compensation type may include at least one of the following: extending the service validity period, providing a benefit package of equivalent value, or reducing part of the service fee.

[0152] Through the above steps S101 to S105, the tariff dispute handling method provided in this application embodiment, in response to a tariff dispute handling request, obtains multi-source business event records associated with the target object and constructs a standard event sequence. Based on the time nodes in the standard event sequence, it generates billing time slices. Based on the billing strategy corresponding to each billing time slice, it determines the billing receivable data for that billing time slice. It compares the billing receivable data with the billed data for each billing time slice to determine the billing difference and the cause of the billing difference. Based on the billing difference and the cause of the billing difference, it determines the tariff dispute handling method. In this way, it achieves fragment-level recalculation and comparison of billing receivable data on the customer service side, providing clear sources of funds and attribution of differences for complex change scenarios. Simultaneously, by combining quantitative correlation analysis of service quality events and network quality indicators, it distinguishes between experience issues and tariff issues, and generates executable handling solutions based on responsibility attribution, effectively improving the accuracy and efficiency of tariff dispute handling.

[0153] In one example, the electronic device can also solidify the data involved in the current tariff dispute resolution process, generate evidence records, generate signature information for the evidence records, and store the signature information in association with the evidence records.

[0154] The data involved in this tariff dispute resolution process may include, but is not limited to: key events in the standard event sequence, billing strategies corresponding to each billing time slice, billing receivable data under each billing time slice, billing differences and the reasons for the billing differences, etc.

[0155] After an electronic device generates an evidence record, it can generate a unique evidence record number and corresponding signature information. The signature information is then associated with the evidence record and stored in the audit storage medium. The evidence record number can be associated with the session number generated in S101, facilitating rapid location and verification of evidence based on the session number.

[0156] In one example, the electronic device uses a hash chain plus timestamp to generate signature information for evidence records, ensuring the immutability and verifiability of the evidence. Specifically, the electronic device first normalizes and concatenates the key content of a single piece of evidence to obtain a digest value. Abstract value This can be expressed by the following formula: in, For the input data snapshot, For the rule to hit the ordered list, For the billing status table summary, For billing and receivable data, For the list of differences, As the attribution analysis results, These are the parameters included in the tariff dispute resolution method.

[0157] Next, the electronic device can generate a chain of signatures in chronological order within the sequence of evidence. Where sig0 is the system initialization seed or the seed value provided by the trusted timestamp service. This is the current timestamp.

[0158] Signature information and evidence records can be written together to an append-only audit storage medium. During subsequent review, this can be verified through recalculation. And compare along the chain i Consistency is used to verify the integrity of evidence; if any link is modified, the chain verification fails.

[0159] In one example, the electronic device can also generate a corresponding searchable index for each evidence record. The index can include keys such as evidence record number, related work order number, UID, DID, billing period and time window, and support quick location of the corresponding evidence by work order number or session number and trigger recalculation comparison.

[0160] In one example, after generating a tariff dispute resolution method, the electronic device can also generate or associate a corresponding work order (hereinafter referred to as the target work order) in the work order system based on the tariff dispute resolution method. In another example, the electronic device automatically fills in the suggested refund amount, relationship repair steps, on-site inspection arrangement, evidence record number, etc. from the tariff dispute resolution method as work order fields and triggers the approval or dispatch process.

[0161] In one example, the electronic device can determine and record the real-time processing status (or current execution status) of the target work order. This real-time processing status can be displayed on the front-end interface for the user to view.

[0162] In one example, electronic devices can write back key status, amounts, and processing suggestions to the customer relationship management system and / or billing and customer service systems to ensure consistency in subsequent inquiries and settlements.

[0163] In one example, the electronic device can also display session information and a tariff dispute resolution method for the tariff dispute resolution request on the interface, and execute the tariff dispute resolution method in response to the operation instructions for the tariff dispute resolution method.

[0164] Specifically, the electronic device can automatically display basic information about the target object, recent event sequence, billing difference, reason for the billing difference, attribution of responsibility, and executable operation buttons in the embedded interface of the customer service platform, using the session number, work order number, handling plan, and evidence record number as inputs in the front-end interface. Customer service personnel can view the above information on the same interface and execute the corresponding handling operation in the tariff dispute handling method by triggering front-end operation instructions. In one example, the handling operation may include at least one of the following: refund operation, relationship repair operation, or compensation operation. The system updates the status immediately after each operation and appends the new operation record to the corresponding evidence record.

[0165] In one example, the electronic device stores key input snapshots, intermediate calculation results, amount calculation records, rule records, and execution logs from the current tariff dispute resolution process as audit data in a read-only audit storage medium, while also recording the version number and timestamp. Authorized personnel can then directly reconstruct the input data, policy parameters, and output conclusions at that time using the evidence record number or session number during subsequent review. They can also recalculate using the same inputs when necessary to verify the consistency of the values.

[0166] The time-slice-based tariff dispute processing apparatus provided in this application is described below. The time-slice-based tariff dispute processing apparatus described below can be referred to in correspondence with the time-slice-based tariff dispute processing method described above.

[0167] Figure 2 This example illustrates a schematic diagram of a time-slice-based tariff dispute resolution device, which includes: The acquisition module 201 is used to respond to a tariff dispute handling request, acquire multi-source business event records associated with the target object, and construct a standard event sequence based on the multi-source business event records.

[0168] The generation module 202 is used to generate billing time slices based on time nodes in a standard event sequence.

[0169] The first determining module 203 is used to determine the billing receivable data under each billing time slice based on the billing strategy corresponding to each billing time slice.

[0170] The second determining module 204 is used to compare the billing receivable data and the billed data under each billing time slice to determine the billing difference and the reason for the billing difference.

[0171] The third determination module 205 is used to determine the method for handling tariff disputes based on the billing difference and the reason for the billing difference.

[0172] Figure 3 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 3 As shown, the electronic device may include a processor 301, a communications interface 302, a memory 303, and a communication bus 304. The processor 301, communications interface 302, and memory 303 communicate with each other via the communication bus 304. The processor 301 can call logical instructions in the memory 303 to execute a time-slice-based tariff dispute resolution method. This method includes: in response to a tariff dispute resolution request, acquiring multi-source business event records associated with the target object, constructing a standard event sequence based on the multi-source business event records, generating a billing time slice based on the time nodes in the standard event sequence; determining the billing receivable data under each billing time slice based on the billing strategy corresponding to each billing time slice; comparing the billing receivable data and the billed data under each billing time slice to determine the billing difference and the cause of the billing difference; and determining the tariff dispute resolution method based on the billing difference and the cause of the billing difference.

[0173] Furthermore, the logical instructions in the aforementioned memory 303 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0174] On the other hand, this application also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the time-slice-based tariff dispute handling method provided by the above methods. The method includes: in response to a tariff dispute handling request, acquiring multi-source business event records associated with a target object, constructing a standard event sequence based on the multi-source business event records, and generating a billing time slice based on the time nodes in the standard event sequence; determining the billing receivable data under each billing time slice based on the billing strategy corresponding to each billing time slice; comparing the billing receivable data and the billed data under each billing time slice to determine the billing difference and the cause of the billing difference; and determining the tariff dispute handling method based on the billing difference and the cause of the billing difference.

[0175] In another aspect, this application also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program is implemented to perform the time-slice-based tariff dispute handling method provided by the above methods. The method includes: in response to a tariff dispute handling request, acquiring multi-source business event records associated with a target object, constructing a standard event sequence based on the multi-source business event records, and generating a billing time slice based on the time nodes in the standard event sequence; determining the billing receivable data under each billing time slice based on the billing strategy corresponding to each billing time slice; comparing the billing receivable data and the billed data under each billing time slice to determine the billing difference and the cause of the billing difference; and determining the tariff dispute handling method based on the billing difference and the cause of the billing difference.

[0176] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0177] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0178] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A time slice-based tariff dispute processing method, characterized by, The method includes: In response to a tariff dispute resolution request, obtain multi-source business event records associated with the target object, and construct a standard event sequence based on the multi-source business event records; Based on the time nodes in the standard event sequence, a billing time slice is generated; Based on the billing strategy corresponding to each billing time slice, determine the billing receivable data under the billing time slice; The billing receivable data and billed data under each billing time slice are compared to determine the billing difference and the reason for the billing difference; Based on the billing difference and the reasons for the billing difference, a method for handling billing disputes is determined.

2. The method of claim 1, wherein, In response to a tariff dispute resolution request, the process of obtaining multi-source business event records associated with the target object and constructing a standard event sequence based on the multi-source business event records includes: In response to a tariff dispute resolution request, the identification information of the target object carried in the tariff dispute resolution request is parsed. Based on the identification information, obtain multiple original event records associated with the target object from multiple business systems; The multiple original event records are deduplicated; The multiple original event records after deduplication are converted into standard events in a unified format to obtain the standard event sequence.

3. The method according to claim 1 or 2, characterized in that, The step of generating a billing time slice based on the time nodes in the standard event sequence includes: The billing time slice is generated using the billing period boundary in the standard event sequence and the occurrence time of the business change event as the dividing point. The business change event includes at least one of the following: subscription event, change event, or cancellation event.

4. The method according to claim 1, characterized in that, The billing strategy includes at least one of the following: package billing rules, fee conversion method, discount stacking rules, trial deduction rules, product mutual exclusion relationship, amount rounding rules, upper limit of billing amount, lower limit of billing amount, and automatic renewal enabled status.

5. The method according to claim 1 or 2, characterized in that, The method for handling tariff disputes, determined based on the billing difference and the reason for the billing difference, includes: The attribution of responsibility is determined based on the billing difference, the reason for the billing difference, and the preset liability determination rules. The method for handling tariff disputes is generated based on the attribution of responsibility and the billing difference.

6. The method according to claim 5, characterized in that, The liability determination rules include platform-side determination conditions and user-side determination conditions. The platform-side determination conditions are used to limit the liability to the platform side, and the user-side determination conditions are used to limit the liability to the user.

7. The method according to claim 5, characterized in that, The step of determining liability based on the billing difference, the cause of the billing difference, and preset liability determination rules includes: Extract service quality events and network quality metrics from the standard event sequence; A quantitative correlation analysis with time window alignment is performed on the service quality events and the network quality indicators to obtain the attribution analysis results; Based on the attribution analysis results, the billing difference, the reasons for the billing difference, and the preset liability determination rules, the liability attribution is determined.

8. The method according to claim 7, characterized in that, The service quality events include playback anomaly events, and the network quality indicators include network latency, packet loss rate, and available bandwidth. The quantitative correlation analysis of the service quality events and network quality indicators, aligned with time windows, to obtain attribution analysis results includes: The playback abnormal events are statistically analyzed according to a preset time window to obtain a playback abnormality ratio sequence within each preset time window. The playback abnormality ratio sequence is used to characterize the change of the ratio of the number of playback abnormal events to the total number of playback events within each preset time window over time. The network latency, packet loss rate, and available bandwidth are statistically analyzed according to the preset time window to obtain a network quality index sequence within each preset time window; the network quality index sequence is used to characterize the change of the measured value of the network quality index over time within each preset time window; Determine the correlation between the playback anomaly ratio sequence and the network quality indicator sequence; Determine the occurrence ratio of abnormal time windows in the abnormal playback ratio sequence. The occurrence ratio of abnormal time windows refers to the ratio of the number of abnormal time windows to the total number of preset time windows. The attribution analysis results are determined based on the correlation and the proportion of occurrence of the abnormal time windows.

9. The method according to claim 1 or 2, characterized in that, The method further includes: The data involved in this tariff dispute resolution process will be documented and used to generate evidence records. Generate signature information for the evidence record; The signature information is associated with and stored in relation to the evidence record.

10. The method according to claim 1 or 2, characterized in that, The method further includes: Based on the aforementioned tariff dispute handling method, a target work order is generated or associated in the work order system.

11. The method according to claim 10, characterized in that, The method further includes: Determine and record the real-time processing status of the target work order.

12. The method according to claim 1 or 2, characterized in that, The method further includes: The interface displays the session information of the tariff dispute resolution request and the tariff dispute resolution method; In response to the operation instruction for the tariff dispute resolution method, the tariff dispute resolution method is executed.

13. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the time-slice-based tariff dispute resolution method as described in any one of claims 1 to 12.

14. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the time-slice-based tariff dispute resolution method as described in any one of claims 1 to 12.

15. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the time-slice-based tariff dispute resolution method as described in any one of claims 1 to 12.

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