Forum Thread Topic Relevance Analysis for QA Ingestion
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Solution Overview
Problem
Current question answering (QA) systems do not effectively utilize the conversational nature of online forums, failing to detect when threads stray off-topic or diverge to useful conclusions, and cannot accurately ingest and analyze the subtle information present in conversational content.
Innovation Solution
An approach that analyzes posts within threads by identifying the main topic, determining the relevance of child posts to the parent post, and selectively ingesting relevant data into a QA system's corpus, maintaining the conversational flow and sentiment levels to enhance the QA system's understanding and response generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the entire forum thread is ingested as a single message body, then the complete conversational content is captured, but the ability to detect off-topic deviations and maintain relevance is lost
Solution Approach 1:
The patent segments the forum thread into individual posts while maintaining hierarchical relationships (parent-child structure). Each post is analyzed separately for topic relevance against the main thread topic, enabling precise detection of off-topic deviations while preserving the complete conversational context through structured ingestion.
2Stability of the object's composition
If traditional ingestion processes maintain the parent-child structure of conversational nodes, then the hierarchical structure is preserved, but the ability to tie posts to one another and detect convergence is lost
Solution Approach 1:
The system implements feedback mechanisms by analyzing each post's relevance to the main thread topic and using this information to determine ingestion. The structured data model maintains parent-child relationships while adding relevance metadata that enables detection of conversational convergence and off-topic deviations, creating a feedback loop for quality control.
3Quantity of substance
If all forum posts are ingested into the corpus, then comprehensive coverage is achieved, but the QA system's response accuracy decreases due to irrelevant information
Solution Approach 1:
The patent applies local quality by differentiating the ingestion of posts based on their individual relevance to the main thread topic. Posts are evaluated locally against topic criteria, and only those meeting relevance thresholds are ingested. This selective approach maintains comprehensive coverage of relevant content while filtering out irrelevant information that would degrade response accuracy.
Data Source
AI summary
An approach is provided to analyze posts included threads of an online forum. The analyzing identifies a main topic related to a parent post of the thread. Child posts of the thread are selected with the parent post being a parent to each of the child posts. Child topics are identified for each of the child posts. A relevance of each of the child posts is determined by comparing the identified main topic to each of the identified child topics. Child posts are selected based on the relevance of the child posts. Parent post data is ingested into a corpus utilized by a question answering (QA) system. Data from the selected child posts is also ingested into the corpus.