Question Search System Topic Focus Segmentation
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Solution Overview
Problem
Current Q&A services cannot accurately determine which questions are most relevant to a queried question, as they treat questions as plain text and lack a method to differentiate between questions with similar meanings but different wording.
Innovation Solution
A question search system that identifies topics and focuses of questions using a minimum description length tree cut model, generating a score based on language models for topic and focus probabilities, and incorporating a mixture model to account for lexical differences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Q&A services treat questions as plain text and use traditional search techniques, then the system complexity remains low, but the measurement precision of question relevance is insufficient
Solution Approach 1:
The patent segments each question into two distinct components: a topic (major context/constraint) and a focus (specific aspects or descriptive features). This segmentation allows the system to analyze questions with finer granularity, improving relevance determination by separating the general subject matter from the specific details the user is interested in.
Solution Approach 2:
The patent introduces a new dimensional framework for question analysis by adding the focus component to the traditional topic-only approach. This dimensional expansion enables the system to capture both the broad topic and the specific aspects of interest, thereby improving measurement precision without simply adding more complexity to the existing structure.
2Measurement precision
If Q&A services use traditional vector space models and language models, then the ease of operation is maintained, but the measurement precision for distinguishing questions with similar meanings but different wording is insufficient
Solution Approach 1:
The patent applies local quality by analyzing different parts of the question with different levels of detail. The topic portion is analyzed for broad categorization, while the focus portion is analyzed for specific aspect matching. This localized analysis approach enables the system to distinguish between questions with similar meanings but different wording by examining the specific focus aspects rather than treating the entire question uniformly.
Data Source
AI summary
A method and system for determining the relevance of questions to a queried question based on topics and focuses of the questions is provided. A question search system provides a collection of questions with topics and focuses. Upon receiving a queried question, the question search system identifies a queried topic and queried focus of the queried question. The question search system generates a score indicating the relevance of a question of the collection to the queried question based on a language model of the topic of the question and a language model of the focus of the question.