Dynamic Topic Tracking in Electronic Textual Conversations
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Solution Overview
Problem
Existing methods fail to effectively collect and organize vast amounts of real-time electronic conversations across multiple social media platforms, especially during breaking news or major events, due to the sheer volume and dynamic nature of the data, which traditional indexing-based searches cannot handle.
Innovation Solution
A system and method that selects primary terms related to a topic, sends queries to communication services, receives and processes messages, extracts additional terms, and dynamically updates a list of secondary terms based on frequency and relevance, while filtering out spam and duplicates, to efficiently follow and collect relevant conversations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional indexing-based searches are used to locate electronic conversations, then the search method is simple and straightforward, but the system cannot handle the sheer volume and dynamic nature of real-time conversation data across multiple platforms
Solution Approach 1:
The patent segments the search system into multiple specialized components: query generation modules that create search queries from seed terms, query execution modules that search across different communication services, message collection modules that gather results, and analysis modules that process the collected data. This segmentation allows each component to handle specific aspects of the overwhelming data volume efficiently, resolving the contradiction between handling large data volumes and maintaining system manageability.
Solution Approach 2:
The patent introduces intermediary components that mediate between the simple search request and the complex data environment. Query generation modules act as intermediaries that translate user intent into multiple search queries across different platforms. Message collection modules serve as intermediaries that aggregate results from various communication services. These intermediaries shield the user from the underlying complexity while enabling the system to handle vast amounts of data.
2Loss of information
If the system collects all messages from multiple communication services, then the completeness of information is improved, but the amount of irrelevant data and spam increases
Solution Approach 1:
The patent implements feedback mechanisms where collected messages are analyzed to generate insights about the conversation topic, which then inform subsequent query generation. The system uses feedback from message analysis to refine search terms, adjust query parameters, and identify emerging sub-topics. This feedback loop enables the system to maintain completeness of relevant information while filtering out spam by continuously adapting to the actual conversation content and quality signals.
Solution Approach 2:
The patent dynamically changes search parameters based on the collected data. Query generation modules adjust search terms, filters, and parameters based on analysis of incoming messages. The system modifies its collection strategy by changing parameters such as search keywords, platform priorities, and filtering thresholds based on the evolving conversation landscape. This dynamic parameter adjustment allows the system to maintain information completeness while adapting to minimize spam and irrelevant data.
3Measurement precision
If the system dynamically generates and updates search terms based on message content, then the relevance of collected conversations is improved, but the computational resources and processing time increase
Solution Approach 1:
The patent performs preliminary actions by pre-generating multiple query variations from seed terms before actual message collection begins. The system pre-processes seed topics to create comprehensive initial search queries across different communication services. This preliminary query generation reduces the need for extensive real-time term modification during data collection, as the system is already equipped with a broad set of search terms to capture relevant conversations, thus balancing relevance with processing efficiency.
Solution Approach 2:
The patent implements periodic updates to search terms rather than continuous real-time modification. The system generates and updates search queries at scheduled intervals or based on thresholds of collected data, rather than continuously analyzing every message and immediately adjusting queries. This periodic action reduces computational overhead while still maintaining high relevance by capturing emerging topics and terminology at appropriate intervals during the conversation monitoring process.
Data Source
AI summary
A method for following a topic in an electronic textual conversation, the method includes selecting, by a computing device, one or more primary terms related to a topic, sending, by the computing device, to at least one communication service, a first query containing the at least one primary term, receiving, by the computing device, from the at least one communication service, at least one first set of messages responsive to the first query, for each first set, extracting, by the computing device, from the first set of messages, a first plurality of additional terms, and for each term of the first plurality of additional terms, enumerating, by the computing device, the messages of the first set in which the term appears and adding the term to a list of secondary terms if the enumeration exceeds a threshold amount.