Social Network Message Insertion Using Suffix Tree Similarity
Solution Overview
Problem
Current social network content presentation systems, such as digital signage and web applications, face challenges in effectively targeting the right population with advertisements due to reliance on predefined keywords, which are difficult to define and measure for relevance.
Innovation Solution
A method that collects and compares social network messages to determine sets of messages with similarity, extracts topics, and inserts corresponding messages, such as advertisements, using suffix trees and joint complexity algorithms, ensuring relevance and high algorithmic efficiency without requiring keyword definitions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If predefined keywords are used for advertisement insertion, then the advertisement targeting can be implemented, but it is difficult to define and measure keyword relevance and impact
Solution Approach 1:
The patent replaces the manual keyword-based mechanical system with an automated topic detection system using joint complexity algorithms. Instead of manually defining keywords and measuring their impact, the system automatically analyzes social network messages to extract topics and determines advertisement relevance through computational complexity measurements, eliminating the need for manual keyword management while improving measurability
Solution Approach 2:
The system enables self-service by automatically detecting topics from social network messages and matching them with advertisements without requiring human intervention for keyword definition or relevance assessment. The joint complexity algorithm autonomously determines topic-advertisement pairs, making the system self-sufficient in terms of keyword management and relevance measurement
2Measurement precision
If topic extraction and similarity comparison methods are implemented, then advertisement relevance is improved, but computational complexity increases
Solution Approach 1:
The patent segments the problem into distinct phases: first collecting social network messages, then determining similarity sets among messages, extracting topics from these sets, and finally comparing topics with advertisements using suffix trees. This segmentation allows the system to manage computational complexity by breaking down the overall task into smaller, more manageable sub-tasks that can be processed sequentially
Solution Approach 2:
The system performs preliminary actions by first collecting and preprocessing social network messages, then determining similarity sets and extracting topics before the actual advertisement matching occurs. By preparing the data structure (topics and similarity sets) in advance, the system reduces the computational burden during the advertisement insertion phase, as the complex analysis has already been performed on the message corpus
Data Source
AI summary
A method, system, and devices for online inserting messages in at least one social network content application of a plurality of social network content applications of at least one social network platform is described. The method includes collecting a plurality of social network messages originating from the plurality of social network content applications, determining a set of messages having a certain degree of similarity from the plurality of social network messages, by comparing each message with each further message of the plurality of message, extracting a topic from the plurality of social network messages included in the set of messages having at least the certain degree of similarity, and determining a second certain degree of similarity between the topic and an second message of a plurality of second messages based on the degree of similarity between respective suffix trees corresponding to each message of the messages.