Question Answer Matching With Candidate Relationship Scoring

The matching process is divided into two distinct stages: first, Pointwise matching is performed between the user input and each candidate question individually to obtain initial similarity scores; second, a relationship analysis stage is introduced to compute correlation coefficients between candidate questions and adjust scores based on their interrelationships. This segmentation allows each stage to optimize for its specific function while collectively achieving both speed and accuracy.

A score adjustment module is introduced as an intermediary between the initial Pointwise matching and the final question-answer pair determination. This module computes relationship scores between candidate questions and uses them to adjust the initial similarity scores, ensuring that both individual question matching and inter-question relationships are considered in the final ranking.

Relationship scores between candidate questions are pre-computed and stored before the actual matching process. When a user input is received, these pre-computed relationship scores are directly applied to adjust the similarity scores without performing additional complex calculations during the matching phase, significantly reducing real-time computational complexity.

The system transforms the complex relationship analysis problem into a parameter adjustment problem by computing correlation coefficients between candidate questions. These coefficients serve as adjustable parameters that modify the initial similarity scores through a simple linear combination, converting a complex relational reasoning task into a manageable parameter-based adjustment process.