Subscriber Activity Scheduling for Message Delivery Accuracy
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional methods for delivering advertisements in communication networks often result in 'dead pings' due to messages being sent to unreachable subscribers, causing network overload and inconvenience, with no effective means to guarantee targeted delivery.
Innovation Solution
A method and system that schedules message transmission based on statistical characteristics of subscriber behavior, including temporal activity history, to determine the probability of a subscriber's presence and activity, reducing unnecessary transmissions and improving delivery efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If advertisement messages are broadcast to mass markets using conventional methods, then the coverage area is large, but the delivery accuracy to appropriate recipients deteriorates
Solution Approach 1:
The patent segments the mass market into targeted subscriber groups based on statistical behavior characteristics. Instead of broadcasting to all subscribers, the system divides the audience into segments that match the advertisement's target profile, thereby maintaining large coverage area while improving delivery accuracy to appropriate recipients.
Solution Approach 2:
The system changes the parameter of message delivery from universal broadcasting to selective targeting based on statistical parameters. By using subscriber behavior statistics (activity patterns, presence probability), the system transforms the delivery mechanism to target specific parameter-matched subscribers rather than all subscribers equally.
2Measurement precision
If presence information is queried for all subscribers before message transmission, then the delivery accuracy improves, but the network load increases
Solution Approach 1:
Instead of querying presence information for all subscribers (excessive action), the system queries only for the subset of subscribers who match the advertisement's target profile based on statistical characteristics (partial action). This reduces the number of presence queries from the total subscriber base to only the relevant targeted group, thereby improving delivery accuracy while reducing network load.
Solution Approach 2:
The system performs preliminary filtering of subscribers based on statistical behavior characteristics before conducting presence queries. By pre-identifying the target subscriber group using historical activity data and behavior patterns, the system avoids unnecessary presence checks for non-targeted subscribers, thus reducing overall network load while maintaining delivery accuracy.
3Speed
If messages are transmitted without scheduling based on subscriber activity, then the transmission speed is fast, but the effectiveness of message delivery deteriorates
Solution Approach 1:
The system performs preliminary analysis of subscriber behavior statistics and activity patterns before message transmission. By pre-calculating the optimal transmission timing based on historical activity data and presence probability, the system ensures messages are sent at the most effective moment without significantly delaying transmission, thus maintaining speed while improving delivery effectiveness.
Solution Approach 2:
The system uses feedback from historical subscriber activity data to optimize message transmission timing. By analyzing past behavior patterns and using this feedback to determine optimal send times, the system improves message effectiveness while maintaining efficient transmission speed through automated decision-making rather than manual intervention.
4Measurement precision
If the HLR is queried excessively for presence information, then the delivery accuracy improves, but the network performance deteriorates
Solution Approach 1:
The system applies partial querying by limiting HLR presence information requests to only those subscribers who match the advertisement's target profile based on statistical behavior characteristics. Instead of querying all subscribers or using excessive queries, the system queries precisely the necessary subset, thereby maintaining presence information accuracy while preserving network performance by avoiding unnecessary HLR load.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
The invention relates to a solution for scheduling transmission of messages, such as advertisement messages, targeted to one or more subscribers (111, 112) of a communication network (103). The transmission of the messages is scheduled at least partly on the basis of statistical characteristics of behaviour of the subscribers. The statistical characteristics of the behaviour of the subscribers are based at least partly on temporal history of activity of the subscribers in the communication network and are formed using appropriate statistical methods on the basis of observed activity of the subscribers. The statistical characteristics of behaviour of the subscribers can be used for reducing a number of messages that are targeted to subscribers not accessible via the communication network at a given time and/or for avoiding transmissions at times that are inappropriate or inconvenient from the viewpoint of a subscriber.