An intelligent voice outbound calling platform

Abstract

The present invention relates to the field of automatic dialing technology, specifically to an intelligent voice outbound call platform, the platform including a network monitoring module, a cost calculation module, a geographic matching module, a time optimization module, a selection adjustment module, and a call encryption module. In the present invention, by associating the success rate of intelligent voice outbound calls with costs and conducting cost-benefit analysis, resource allocation is made more accurate, service quality and customer satisfaction are improved, and by matching customer geographic locations and needs, services are made more personalized and responsive faster, dialing strategies are adjusted to adapt to network channel usage and congestion, call quality and cost efficiency are further optimized, and the network is dynamically adjusted to capture the optimal balance point between cost and performance. In a constantly changing network environment, users can always obtain the best service experience, reduce enterprise operating costs, enhance user experience through customized communication methods, and have a revolutionary impact on the operation of call centers.

Description

Technical Field

[0001] The present invention relates to the technical field of automatic dialing, and in particular to an intelligent voice outbound calling platform. Background Art

[0002] The field of autodialing technology focuses on using automation platforms to initiate phone calls. It is applied to call centers, customer service centers and marketing activities, with the goal of improving work efficiency and reducing the need for manual phone calls. The autodialing platform can automatically dial phone numbers according to a preset list and transfer the call to a live operator or play a pre-recorded message after the call is connected. It can be further integrated with speech recognition platforms, artificial intelligence and machine learning algorithms to optimize response strategies, analyze call content and provide personalized services. The development of autodialing technology also includes complex algorithms to manage call timing, optimize call distribution and comply with laws and regulations, such as preventing frequent meaningless calls.

[0003] Among them, the intelligent voice outbound call platform is a platform that integrates automatic dialing technology and voice processing technology. It is designed to automate the telephone call process and provide a highly interactive customer service experience. It uses the automatic dialing function to effectively manage batch outbound call activities, while integrating voice recognition and natural language processing technology to enable the platform to understand and respond to customer voice input. Intelligent voice outbound call platforms are widely used in customer support, marketing promotion, and information broadcasting. They can significantly improve communication efficiency, reduce corporate operating costs, and enhance user experience by providing customized communication methods. The popularity of the platform is a revolutionary improvement for call center operations, enabling companies to maintain high efficiency while maintaining good customer relationships.

[0004] Although the existing automatic dialing technology can manage batch calls and improve efficiency, it lacks adaptability to network status and in-depth analysis of cost-effectiveness. In actual operation, especially in complex or unstable network conditions, it leads to inconsistent service quality and customer experience. For example, the automatic dialing platform still blindly initiates calls when the network is congested, resulting in high call failure rates and inefficient resource utilization, which is particularly fatal in the fields of customer service and marketing. Existing technologies do not make full use of geographic and time data to optimize dialing strategies, resulting in the inability to provide personalized services based on customers' actual needs and locations, which puts them at a disadvantage in the fierce market competition. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an intelligent voice outbound calling platform.

[0006] In order to achieve the above object, the present invention adopts the following technical solution, an intelligent voice outbound calling platform includes:

[0007] The network monitoring module generates network performance data by monitoring the delay of multiple network channels, recording the packet loss rate and data transmission speed, analyzing and recording performance indicators;

[0008] The cost calculation module uses the network performance data to calculate the cost of the differentiated intelligent voice outbound call channel, associates the intelligent voice outbound call success rate with the cost, and outputs a cost-benefit analysis result;

[0009] The geographic matching module uses the cost-benefit analysis results, combines the customer's geographic location, and refers to the user's real-time changing needs to perform matching analysis between the geographic location and the intelligent voice outbound call network status, and outputs the target network configuration;

[0010] The time optimization module adopts the target network configuration, adjusts the time and user selection of intelligent voice outbound calls according to the network channel usage and congestion in differentiated time periods, and constructs an adjustment dialing strategy;

[0011] The selection adjustment module optimizes the selection of the intelligent voice outbound call network based on the adjusted dialing strategy, captures the optimal balance point between the cost and performance of the intelligent voice outbound call by dynamically adjusting the network, and outputs the network selection strategy;

[0012] The call encryption module allocates encryption keys for intelligent voice outbound calls according to the network selection strategy, verifies the data security of the calls by managing the use of the keys in real time, and outputs the outbound encryption verification results.

[0013] As a further solution of the present invention, the network performance data includes delay indicators, packet loss rates and data transmission speeds of differentiated channels, the cost-benefit analysis results include channel operating costs, call success rates and cost comparison analysis results, the target network configuration includes optimal channel selection and priority setting, the adjusted dialing strategy includes dialing time and channel selection strategies that are differentially adjusted according to network congestion conditions and time periods, the network selection strategy includes optimized network routing and connection priority, and the outbound call encryption verification results include encryption key management and verification records, key validity and encryption strength verification of intelligent voice outbound calls.

[0014] As a further solution of the present invention, the network monitoring module includes:

[0015] The network monitoring submodule monitors the delay of multiple network channels, cyclically captures the delay data of differentiated network channels, records it in combination with the timestamp of intelligent voice outbound calls, analyzes the change trend of the data, and generates delay monitoring data;

[0016] The data recording submodule extracts key information from the delay monitoring data, identifies the usage record of the network channel in combination with the packet loss rate and data transmission speed of the network channel, and generates a network transmission record;

[0017] The performance analysis submodule uses the network transmission records to analyze the data of differentiated network channel usage, evaluates network performance in multiple dimensions, and obtains network performance data.

[0018] As a further solution of the present invention, the cost calculation module includes:

[0019] The cost accounting submodule calculates the operating cost of the differentiated intelligent voice outbound call channel based on the network performance data, calculates the operating cost of the intelligent voice outbound call channel with reference to the impact of network quality on cost fluctuations, and generates channel cost data;

[0020] The success rate analysis submodule uses the channel cost data to analyze the success rate of intelligent voice outbound calls, associates the call success rate with the differentiated channel cost, analyzes the relationship between the cost and the success rate, and outputs the cost success rate association data;

[0021] The benefit calculation submodule extracts key indicators from the cost-success rate associated data, evaluates the optimal ratio of cost to success rate, formulates a cost-benefit balance strategy, and obtains a cost-benefit analysis result.

[0022] As a further solution of the present invention, the geographic matching module includes:

[0023] The location positioning submodule analyzes regional characteristics and user distribution based on the cost-benefit analysis results and the geographical location information of differentiated users, evaluates the influencing factors of geographical location on intelligent voice outbound calls, and generates geographical analysis data;

[0024] The demand analysis submodule uses the geographic analysis data and a clustering algorithm to identify the geographic areas associated with the intelligent voice outbound call demand, dynamically matches the user's demand in real time, and outputs the demand matching result;

[0025] The network configuration submodule optimizes the configuration of the intelligent voice outbound call network according to the demand matching results, analyzes the optimal network channel selection, checks the optimal match between the geographical location and the network status, and obtains the target network configuration.

[0026] As a further solution of the present invention, the formula of the clustering algorithm is as follows:

[0027]

[0028] in, is the total sum of squared distances, For sample The total number of For clustering The number of is the indicator variable, is the weight coefficient, For geographic location data, is the cluster center, For the intensity of user demand, is the demand intensity center, For time sensitivity, For time-sensitive centers, is the geographical distance, is the demand intensity distance, is the time sensitivity distance.

[0029] As a further solution of the present invention, the time optimization module includes:

[0030] The time analysis submodule analyzes the network channel usage data of the differentiated time periods based on the target network configuration, records the network activities and user behavior patterns in each time period, identifies the peak and valley of the network load, and generates the time usage data;

[0031] The network status assessment submodule uses the time usage data to assess the network congestion, identify the load period and channel, record the network congestion status through real-time monitoring, and output the congestion assessment result;

[0032] The strategy formulation submodule adjusts the time setting and user selection parameters of the intelligent voice outbound call according to the congestion assessment results, combined with the user's calling habits and network status, optimizes the dialing timing and channel allocation, checks the quality and efficiency of the intelligent voice outbound call, and obtains an adjusted dialing strategy.

[0033] As a further solution of the present invention, the selection and adjustment module includes:

[0034] The strategy analysis submodule uses a decision tree algorithm based on the adjusted dialing strategy to analyze the correlation between the intelligent voice outbound calling behavior and the dialing strategy, evaluate the adaptability and efficiency of the strategy, analyze the adjustment requirements of the strategy, and generate strategy optimization data;

[0035] The network adjustment submodule uses the strategy optimization data to implement dynamic adjustment of network configuration, adjust channel allocation and network routing according to real-time network performance feedback, optimize the quality of intelligent voice outbound call communication, and output network optimization results;

[0036] The balance point positioning submodule extracts key performance indicators from the network optimization results, and compares and analyzes them with cost data, analyzes the optimal balance point of cost-effectiveness, verifies the cost and performance optimization of intelligent voice outbound calls, and obtains a network selection strategy.

[0037] As a further solution of the present invention, the formula of the decision tree algorithm is as follows:

[0038]

[0039] in, is the Gini impurity, For nodes belonging to the category The probability of is the total number of categories, is a collection of additional reference attributes. For attribute set Middle The value of the attribute, For attribute set The average value of For the The weight of the attribute, is the weight coefficient, For attribute set The number of

[0040] As a further solution of the present invention, the call encryption module includes:

[0041] The key distribution submodule dynamically distributes encryption keys for intelligent voice outbound calls based on the network selection strategy, and reviews the authority for using the encryption keys to generate encrypted key data;

[0042] The key monitoring submodule utilizes the encrypted key data to implement real-time management and monitoring of the key, update and verify the validity of the key, avoid key leakage and reuse, and output key management results;

[0043] The encryption review submodule uses the key management results to perform encryption verification on the intelligent voice outbound calls, check the integrity of the encryption implementation, verify the security and privacy protection of the call data, and obtain the outbound encryption verification results.

[0044] Compared with the prior art, the advantages and positive effects of the present invention are:

[0045] In the present invention, by monitoring the delay of multiple network channels, recording the packet loss rate and data transmission speed, and analyzing the network performance data, the optimization brought about is significant. The success rate of intelligent voice outbound calls is associated with the cost and a cost-benefit analysis is performed, so that resource allocation is more accurate and service quality and customer satisfaction are improved. By matching the customer's geographic location and needs, combined with the optimized network configuration, the service is more personalized and the response speed is faster. Adjust the dialing strategy to adapt to the network channel usage and congestion to further optimize call quality and cost efficiency. Dynamically adjust the network to capture the optimal balance between cost and performance. The real-time adjustment mechanism ensures that users can always get the best service experience in a constantly changing network environment, which not only reduces the operating costs of the enterprise, but also enhances the user experience through customized communication methods, which has a revolutionary impact on the operation of the call center. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 is a flow chart of the platform of the present invention;

[0047] Figure 2 It is a schematic diagram of the platform framework of the present invention;

[0048] Figure 3 It is a flow chart of the network monitoring module of the present invention;

[0049] Figure 4 is a flow chart of the cost calculation module of the present invention;

[0050] Figure 5 is a flow chart of the geographic matching module of the present invention;

[0051] Figure 6 It is a flow chart of the time optimization module of the present invention;

[0052] Figure 7 The flow chart of the selection and adjustment module of the present invention;

[0053] Figure 8 This is a flow chart of the call encryption module of the present invention. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0055] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0056] See also Figure 1 to Figure 2 , an intelligent voice outbound calling platform includes:

[0057] The network monitoring module monitors the delay of multiple network channels, records the packet loss rate and data transmission speed, analyzes and records performance indicators, identifies the usage records of network channels, evaluates network performance in multiple dimensions, and generates network performance data;

[0058] The cost calculation module uses network performance data to calculate the cost of differentiated intelligent voice outbound channels, and associates the success rate of intelligent voice outbound calls with the cost, evaluates the optimal ratio of cost and success rate, and outputs the cost-benefit analysis results;

[0059] The geographic matching module uses the cost-benefit analysis results, combined with the customer's geographic location, and refers to the user's real-time changing needs to perform a matching analysis between the geographic location and the intelligent voice outbound call network status, and outputs the target network configuration;

[0060] The time optimization module uses the target network configuration to adjust the time and user selection of intelligent voice outbound calls according to the network channel usage and congestion in differentiated time periods, optimize the dialing timing and channel allocation, and build an adjustment dialing strategy;

[0061] The selection and adjustment module optimizes the selection of intelligent voice outbound call networks based on the adjusted dialing strategy. By dynamically adjusting the network, it captures the optimal balance between the cost and performance of intelligent voice outbound calls and outputs the network selection strategy.

[0062] The call encryption module allocates encryption keys for intelligent voice outbound calls based on the network selection strategy, manages the use of keys in real time, avoids key leakage and reuse, verifies the data security of calls, and outputs outbound encryption verification results.

[0063] Network performance data includes delay indicators, packet loss rate and data transmission speed of differentiated channels. Cost-benefit analysis results include channel operating costs, call success rate and cost comparison analysis results. Target network configuration includes optimal channel selection and priority setting. Adjustment of dialing strategy includes dialing time and channel selection strategy adjusted according to network congestion conditions and time periods. Network selection strategy includes optimized network routing and connection priority. Outbound call encryption verification results include encryption key management and verification records, key validity and encryption strength verification of intelligent voice outbound calls.

[0064] See also Figure 2 , 3 , the network monitoring module includes:

[0065] The network monitoring submodule monitors the delay of multiple network channels, cyclically captures the delay data of differentiated network channels, records it in combination with the timestamp of intelligent voice outbound calls, analyzes the change trend of the data, and generates the execution process of delay monitoring data as follows;

[0066] The network monitoring submodule monitors the delay of multiple network channels to ensure the continuity and efficiency of network communication. It cyclically captures the delay data of each network channel and records it in combination with the timestamp of the intelligent voice outbound call platform. By analyzing the data, it is possible to identify the changing trend of network delay and potential network bottlenecks, helping network managers to adjust network configuration or enhance network capacity in a timely manner. Through long-term monitoring and data analysis, future network delay problems can be predicted, providing a scientific basis for network maintenance and generating delay monitoring data. The formula used is:

[0067]

[0068] in, Indicates delayed monitoring data, Indicates The delay of a network channel, is the number of network channels, is the corresponding timestamp.

[0069] The data recording submodule extracts key information from the delay monitoring data, combines the packet loss rate and data transmission speed of the network channel, identifies the usage record of the network channel, and generates the execution process of the network transmission record as follows;

[0070] The data recording submodule extracts key information from the delay monitoring data, and combines the packet loss rate and data transmission speed of the network channel to identify the usage of each network channel, record and analyze the performance indicators of the network, such as delay, packet loss rate and throughput, to identify the stability and efficiency of the network. Through the data, we can better understand the performance of the network under different conditions, and provide empirical data for network optimization, generate network transmission records, and use the formula:

[0071]

[0072] in, Indicates network transmission records. It is Delayed data for each channel, is the number of channels, is the packet loss rate, is the data transfer speed.

[0073] The performance analysis submodule uses network transmission records to analyze the data of differentiated network channel usage, evaluates network performance in multiple dimensions, and obtains the execution process of network performance data as follows;

[0074] The performance analysis submodule uses network transmission records to conduct in-depth analysis of the usage of different network channels, evaluate network performance in multiple dimensions, and analyze the performance data of each channel, such as latency, packet loss rate, and throughput, to identify the strengths and weaknesses of network performance. Through multi-dimensional evaluation, the performance of the network in different scenarios can be revealed, helping administrators target network configuration and improve the overall performance of the network, and obtaining network performance data using the formula:

[0075]

[0076] in, Represents network performance data, is the number of channels, and Respectively represent The latency, packet loss rate, and data transmission speed of each channel.

[0077] See also Figure 2 , 4 , the cost calculation module includes:

[0078] The cost accounting submodule calculates the operating cost of the differentiated intelligent voice outbound call channel based on the network performance data, and refers to the impact of network quality on cost fluctuations to calculate the operating cost of the intelligent voice outbound call channel. The execution process of generating channel cost data is as follows;

[0079] The cost accounting submodule calculates the operating costs of the intelligent voice outbound channel in detail based on network performance data, evaluates the performance of different network channels, including latency, packet loss rate, and data transmission speed, and how these factors affect operating costs. By analyzing the relationship between network quality and cost, it is possible to identify channels where cost increases are caused by inefficient network performance. It also calculates the relationship between the investment required to maintain a high-quality network and the potential cost savings, helping decision makers develop more cost-effective network operation strategies and generate channel cost data using the formula:

[0080]

[0081] in, Indicates the operating cost of the intelligent voice outbound channel. is the number of channels, It is The unit operating cost of each channel is It is The network quality indicator of each channel.

[0082] The success rate analysis submodule uses channel cost data to analyze the success rate of intelligent voice outbound calls, associates the call success rate with differentiated channel costs, analyzes the relationship between cost and success rate, and outputs the execution process of cost success rate association data as follows;

[0083] The success rate analysis submodule uses channel cost data to analyze the success rate of intelligent voice outbound calls and explore the relationship between call success rate and differentiated channel costs. By combining channel costs with call success rates, it is possible to identify the channels with the highest and lowest cost efficiency, providing data support for optimizing resource allocation and cost management. It helps reveal how to improve the overall success rate by improving network performance or adjusting resource allocation, and outputs cost-success rate correlation data, using the formula:

[0084]

[0085] in, Represents cost success rate associated data, is the number of channels, It is The success rate of each channel, is the corresponding operating cost.

[0086] The benefit calculation submodule extracts key indicators from the cost-success rate correlation data, evaluates the optimal ratio of cost and success rate, formulates a cost-benefit balance strategy, and obtains the execution process of the cost-benefit analysis results as follows;

[0087] The benefit calculation submodule extracts key indicators from the cost-success rate correlation data, evaluates the optimal ratio of cost to success rate, and uses the data to develop a cost-benefit balance strategy to maximize return on investment. By comparing the cost-benefit ratios of different channels, it is possible to recommend the best resource configuration and budget allocation strategy to improve overall operational efficiency and customer satisfaction, and obtain the cost-benefit analysis results using the formula:

[0088]

[0089] in, The results of cost-benefit analysis are shown in and Respectively represent The benefits and corresponding costs of the success rate of each channel.

[0090] See also Figure 2 , 5 , the geo-matching module includes:

[0091] The location positioning submodule is based on the cost-benefit analysis results, combined with the geographical location information of differentiated users, analyzes regional characteristics and user distribution, evaluates the factors affecting the geographical location on intelligent voice outbound calls, and generates the execution process of geographical analysis data as follows;

[0092] The location positioning submodule evaluates the factors affecting the outbound intelligent voice calls based on the cost-benefit analysis results and the location information of differentiated users. It deeply analyzes the regional characteristics and user distribution and identifies how specific locations affect the call success rate and cost-effectiveness. Through analysis, it can provide insights on how to adjust service strategies to meet the needs of specific regions. It helps decision makers understand the specific impact of geographical factors on service efficiency and promotes more targeted resource allocation and service optimization. It generates geographic analysis data using the formula:

[0093]

[0094] in, Represents geographic analysis data, is the number of regions, It is The geographical location identifier of the region, is the user distribution density at the geographic location, are cost-effectiveness figures relevant to the region.

[0095] The demand analysis submodule uses geographic analysis data and a clustering algorithm to identify geographic areas associated with intelligent voice outbound call demand, dynamically matches user demand in real time, and outputs the demand matching results. The execution process is as follows;

[0096] The demand analysis submodule uses geographic analysis data and a clustering algorithm to identify geographic areas that are closely related to intelligent voice outbound call demand, classify geographic areas according to demand characteristics, and achieve dynamic matching of user needs. This helps optimize service allocation and ensure that resources are used most effectively geographically. By tracking and analyzing the geographic distribution of user needs in real time, it can provide more accurate service adjustment suggestions and output demand matching results.

[0097] The formula of the clustering algorithm is as follows:

[0098]

[0099] in, is the total sum of squared distances, For sample The total number of For clustering The number of is the indicator variable, is the weight coefficient, For geographic location data, is the cluster center, For the intensity of user demand, is the demand intensity center, For time sensitivity, For time-sensitive centers, is the geographical distance, is the demand intensity distance, is the time sensitivity distance.

[0100] The execution flow is as follows:

[0101] Select Geolocation Data , User demand intensity and time sensitivity As a feature of the sample point set, determine the number of clusters , initialize cluster centers , Demand Intensity Center and time-sensitive centers , for each sample point, calculate and assign it to the nearest cluster center based on the weighted comprehensive distance, weight coefficient Determined by optimization algorithms such as grid search to ensure that the importance of each feature is appropriately reflected, update , update the center point of each cluster , so that Minimize and repeat the above process until the cluster center no longer changes or the preset number of iterations is reached, output the demand category to which each geographic area belongs and the distance from each cluster center, and match user needs with geographic location in real time.

[0102] The network configuration submodule optimizes the configuration of the intelligent voice outbound call network according to the demand matching results, analyzes the optimal network channel selection, checks the optimal match between the geographical location and the network status, and obtains the execution process of the target network configuration as follows;

[0103] The network configuration submodule optimizes the configuration of the intelligent voice outbound call network based on the demand matching results, analyzes the optimal network channel selection, and ensures the best match between the geographical location and the network status. By evaluating the performance and cost-effectiveness of each network channel and its association with the geographical location, it can recommend the most suitable network configuration strategy, which helps to improve call quality and reduce operating costs, and obtain the target network configuration. The formula used is:

[0104]

[0105] in, Indicates the target network configuration result. is the number of channels, It is The service quality score of each channel, It is the performance and cost-effectiveness ratio of the channel.

[0106] See also Figure 2 , 6 , the time optimization module includes:

[0107] The time analysis submodule analyzes the network channel usage data of differentiated time periods based on the target network configuration, records the network activities and user behavior patterns in each time period, identifies the peaks and valleys of network load, and generates the execution flow of time usage data as follows;

[0108] The time analysis submodule deeply analyzes the network channel usage data in differentiated time periods based on the target network configuration, continuously records the network activities and user behavior patterns in each time period, and provides detailed data to identify the peaks and valleys of network load. Time period analysis helps to understand the performance of network channels in a specific period of time, and can predict and prepare the necessary resource allocation to cope with the expected high load, and generate time usage data. The formula used is:

[0109]

[0110] in, Represents time usage data, is the total number of hours, It is Activity level during the hour It is the user behavior data within the same time period.

[0111] The network status assessment submodule uses time usage data to assess the network congestion, identify load periods and channels, and record network congestion status through real-time monitoring and output the congestion assessment results. The execution process is as follows;

[0112] The network status assessment submodule uses time usage data to accurately assess the network congestion. By real-time monitoring and recording the network congestion status, it identifies the peak load period and related channels, which helps to timely discover and solve network congestion problems, ensure the smooth flow of communication channels, and output the congestion assessment results. The formula used is:

[0113]

[0114] in, Indicates the congestion assessment result. is the number of time periods, It is the time period The network load within is the channel capacity during the time period.

[0115] The strategy formulation submodule adjusts the time setting and user selection parameters of intelligent voice outbound calls according to the congestion assessment results, combined with the user's calling habits and network status, optimizes the dialing timing and channel allocation, and checks the quality and efficiency of intelligent voice outbound calls. The execution process of adjusting the dialing strategy is as follows;

[0116] The strategy formulation submodule adjusts the time setting and user selection parameters of intelligent voice outbound calls based on the congestion assessment results, combined with the user's calling habits and network status, and improves the quality and efficiency of intelligent voice outbound calls by optimizing dialing timing and channel allocation. Through strategy adjustment, call attempts during congestion periods can be reduced, user experience and overall service responsiveness can be improved, and the dialing strategy can be adjusted. The formula used is:

[0117]

[0118] in, Indicates the adjusted dialing strategy. Yes Channel The number of is the optimized dialing timing parameter, is the channel allocation parameter.

[0119] See also Figure 2 , 7 , select adjustment modules including:

[0120] The strategy analysis submodule uses a decision tree algorithm to adjust the dialing strategy, analyze the correlation between the intelligent voice outbound calling behavior and the dialing strategy, evaluate the adaptability and efficiency of the strategy, analyze the adjustment needs of the strategy, and generate the execution process of strategy optimization data as follows;

[0121] The strategy analysis submodule uses a decision tree algorithm to analyze the correlation between intelligent voice outbound calling behavior and dialing strategy based on adjusting the dialing strategy. It also uses a decision tree algorithm to analyze the intelligent voice outbound calling data and identify the impact of different dialing strategies on success rate and response time. Through analysis, the adaptability and efficiency of the existing dialing strategy are evaluated to determine whether strategy adjustment is needed and generate strategy optimization data.

[0122] The formula for the decision tree algorithm is as follows:

[0123]

[0124] in, is the Gini impurity, For nodes belonging to the category The probability of is the total number of categories, is a collection of additional reference attributes. For attribute set Middle The value of the attribute, For attribute set The average value of For the The weight of the attribute, is the weight coefficient, For attribute set The number of

[0125] The execution flow is as follows:

[0126] Determine the current node, select the split attribute, and calculate each category The probability of being in the current node , we get the original Gini impurity, for the additional attribute set , calculate each attribute Relative to the average The absolute deviation of , sum the deviations to get the weighted sum of attribute dispersion, and use the coefficient To balance the impact of Gini impurity and attribute dispersion, calculate Value, determine the weight coefficient The value of is determined by cross-validation or AIC (Akaike Information Content) criterion to ensure the generalization ability and accuracy of the model, and the Gini impurity of the node after improvement is calculated as a whole.

[0127] The network adjustment submodule uses strategy optimization data to implement dynamic adjustment of network configuration, adjusts channel allocation and network routing according to real-time network performance feedback, optimizes the quality of intelligent voice outbound communication, and outputs the execution process of network optimization results as follows;

[0128] The network adjustment submodule uses strategy optimization data to implement dynamic adjustments to network configurations. It dynamically adjusts channel allocation and network routing based on real-time network performance feedback. The adjustment is designed to optimize the communication quality of intelligent voice outbound calls and ensure efficient and stable data transmission. By continuously monitoring the network status and adjusting the network configuration, the network optimization results are output. The formula used is:

[0129]

[0130] in, represents the network optimization score, Is an indicator The total number of is a network performance indicator, is the latency indicator, and is the weight factor.

[0131] The balance point positioning submodule extracts key performance indicators from the network optimization results and compares and analyzes them with the cost data to analyze the optimal balance point of cost-effectiveness, verify the cost and performance optimization of intelligent voice outbound calls, and obtain the execution process of the network selection strategy as follows;

[0132] The balance point positioning submodule extracts key performance indicators from the network optimization results and compares and analyzes them with the cost data. The platform analyzes the optimal balance point of cost-effectiveness to verify the cost and performance optimization of intelligent voice outbound calling. The platform can find the best operating point between cost and performance, so that the intelligent voice outbound calling platform can operate in the most economical and effective state and obtain the network selection strategy.

[0133]

[0134] in, represents the cost-benefit balance point, is a performance indicator, is a cost indicator, The parameters considered The total number of .

[0135] See also Figure 2 , 8 , the call encryption module includes:

[0136] The key distribution submodule dynamically distributes encryption keys for intelligent voice outbound calls based on the network selection strategy, and reviews the permissions for using encryption keys. The execution process for generating encrypted key data is as follows;

[0137] The key distribution submodule dynamically allocates encryption keys for intelligent voice outbound calls based on the network selection strategy. The platform determines the appropriate key type and length based on the network selection strategy to adapt to security requirements under different network conditions, dynamically generates encryption keys, and reviews the key usage permissions to ensure that the keys are only used by authorized users and devices to generate encrypted key data.

[0138] The key monitoring submodule uses encrypted key data to implement real-time key management and monitoring, update and verify the validity of keys, avoid key leakage and reuse, and output the key management results. The execution process is as follows;

[0139] The key monitoring submodule uses encrypted key data to implement real-time management and monitoring of keys. The platform continuously updates and verifies the validity of keys to ensure that keys are not illegally copied or leaked. By real-time monitoring of key usage, the platform can promptly detect any abnormal activities, avoid the risk of key leakage and reuse, and output key management results using the formula:

[0140]

[0141] in, Indicates the monitoring status of the key. It is The weight of the key, is the indicator function, is the key, Is the validity period of the key is the total number of keys monitored.

[0142] The encryption review submodule uses the key management results to perform encryption verification on the intelligent voice outbound call, check the integrity of the encryption implementation, and verify the security and privacy protection of the call data. The execution process of obtaining the outbound encryption verification result is as follows;

[0143] The encryption review submodule performs encryption verification on the intelligent voice outbound calls through the key management results. The platform checks the integrity of the encryption implementation to ensure that the encryption process of each call meets the security standards. The platform also verifies the security and privacy protection of the call data and confirms that the data has not been tampered with or leaked during transmission. After a series of verifications, the platform obtains the outbound encryption verification results.

[0144] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. An intelligent voice outbound calling platform, characterized in that: The platform includes: The network monitoring module generates network performance data by monitoring the delay of multiple network channels, recording the packet loss rate and data transmission speed, analyzing and recording performance indicators; The cost calculation module uses the network performance data to calculate the cost of the differentiated intelligent voice outbound call channel, associates the intelligent voice outbound call success rate with the cost, and outputs a cost-benefit analysis result; The geographic matching module uses the cost-benefit analysis results, combines the customer's geographic location, and refers to the user's real-time changing needs to perform matching analysis between the geographic location and the intelligent voice outbound call network status, and outputs the target network configuration; The time optimization module adopts the target network configuration, adjusts the time and user selection of intelligent voice outbound calls according to the network channel usage and congestion in differentiated time periods, and constructs an adjustment dialing strategy; The selection adjustment module optimizes the selection of the intelligent voice outbound call network based on the adjusted dialing strategy, captures the optimal balance point between the cost and performance of the intelligent voice outbound call by dynamically adjusting the network, and outputs the network selection strategy; The call encryption module allocates encryption keys for intelligent voice outbound calls according to the network selection strategy, verifies the data security of the calls by managing the use of the keys in real time, and outputs the outbound encryption verification results.

2. The intelligent voice outbound calling platform according to claim 1, characterized in that: The network performance data includes delay indicators, packet loss rates and data transmission speeds of differentiated channels; the cost-benefit analysis results include channel operating costs, call success rates and cost comparison analysis results; the target network configuration includes optimal channel selection and priority setting; the adjusted dialing strategy includes dialing time and channel selection strategies that are differentially adjusted according to network congestion conditions and time periods; the network selection strategy includes optimized network routing and connection priority; the outbound call encryption verification results include encryption key management and verification records, key validity and encryption strength verification for intelligent voice outbound calls.

3. The intelligent voice outbound calling platform according to claim 1, characterized in that: The network monitoring module includes: The network monitoring submodule monitors the delay of multiple network channels, cyclically captures the delay data of differentiated network channels, records it in combination with the timestamp of intelligent voice outbound calls, analyzes the change trend of the data, and generates delay monitoring data; The data recording submodule extracts key information from the delay monitoring data, identifies the usage record of the network channel in combination with the packet loss rate and data transmission speed of the network channel, and generates a network transmission record; The performance analysis submodule uses the network transmission records to analyze the data of differentiated network channel usage, evaluates network performance in multiple dimensions, and obtains network performance data.

4. The intelligent voice outbound calling platform according to claim 1, characterized in that: The cost calculation module includes: The cost accounting submodule calculates the operating cost of the differentiated intelligent voice outbound call channel based on the network performance data, calculates the operating cost of the intelligent voice outbound call channel with reference to the impact of network quality on cost fluctuations, and generates channel cost data; The success rate analysis submodule uses the channel cost data to analyze the success rate of intelligent voice outbound calls, associates the call success rate with the differentiated channel cost, analyzes the relationship between the cost and the success rate, and outputs the cost success rate association data; The benefit calculation submodule extracts key indicators from the cost-success rate associated data, evaluates the optimal ratio of cost to success rate, formulates a cost-benefit balance strategy, and obtains a cost-benefit analysis result.

5. The intelligent voice outbound calling platform according to claim 1, characterized in that: The geographic matching module includes: The location positioning submodule analyzes regional characteristics and user distribution based on the cost-benefit analysis results and the geographical location information of differentiated users, evaluates the influencing factors of geographical location on intelligent voice outbound calls, and generates geographical analysis data; The demand analysis submodule uses the geographic analysis data and a clustering algorithm to identify the geographic areas associated with the intelligent voice outbound call demand, dynamically matches the user's demand in real time, and outputs the demand matching result; The network configuration submodule optimizes the configuration of the intelligent voice outbound call network according to the demand matching results, analyzes the optimal network channel selection, checks the optimal match between the geographical location and the network status, and obtains the target network configuration.

6. The intelligent voice outbound calling platform according to claim 5, characterized in that: The formula of the clustering algorithm is as follows: in, is the total sum of squared distances, For sample The total number of For clustering The number of is an indicator variable, is the weight coefficient, For geographic location data, is the cluster center, For the intensity of user demand, is the demand intensity center, For time sensitivity, For time-sensitive centers, is the geographical distance, is the demand intensity distance, is the time sensitivity distance.

7. The intelligent voice outbound calling platform according to claim 1, characterized in that: The time optimization module includes: The time analysis submodule analyzes the network channel usage data of the differentiated time periods based on the target network configuration, records the network activities and user behavior patterns in each time period, identifies the peak and valley of the network load, and generates the time usage data; The network status assessment submodule uses the time usage data to assess the network congestion, identify the load period and channel, record the network congestion status through real-time monitoring, and output the congestion assessment result; The strategy formulation submodule adjusts the time setting and user selection parameters of the intelligent voice outbound call according to the congestion assessment results, combined with the user's calling habits and network status, optimizes the dialing timing and channel allocation, checks the quality and efficiency of the intelligent voice outbound call, and obtains an adjusted dialing strategy.

8. The intelligent voice outbound calling platform according to claim 1, characterized in that: The selection and adjustment module comprises: The strategy analysis submodule uses a decision tree algorithm based on the adjusted dialing strategy to analyze the correlation between the intelligent voice outbound calling behavior and the dialing strategy, evaluate the adaptability and efficiency of the strategy, analyze the adjustment requirements of the strategy, and generate strategy optimization data; The network adjustment submodule uses the strategy optimization data to implement dynamic adjustment of network configuration, adjust channel allocation and network routing according to real-time network performance feedback, optimize the quality of intelligent voice outbound call communication, and output network optimization results; The balance point positioning submodule extracts key performance indicators from the network optimization results, and compares and analyzes them with cost data, analyzes the optimal balance point of cost-effectiveness, verifies the cost and performance optimization of intelligent voice outbound calls, and obtains a network selection strategy.

9. The intelligent voice outbound calling platform according to claim 8, characterized in that: The formula of the decision tree algorithm is as follows: in, is the Gini impurity, For nodes belonging to the category The probability of is the total number of categories, is a collection of additional reference attributes. For attribute set Middle The value of the attribute, For attribute set The average value of For the The weight of the attribute, is the weight coefficient, For attribute set The number of 10. The intelligent voice outbound calling platform according to claim 1, characterized in that: The call encryption module includes: The key distribution submodule dynamically distributes encryption keys for intelligent voice outbound calls based on the network selection strategy, and reviews the authority for using the encryption keys to generate encrypted key data; The key monitoring submodule utilizes the encrypted key data to implement real-time management and monitoring of the key, update and verify the validity of the key, avoid key leakage and reuse, and output key management results; The encryption review submodule uses the key management results to perform encryption verification on the intelligent voice outbound calls, check the integrity of the encryption implementation, verify the security and privacy protection of the call data, and obtain the outbound encryption verification results.

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