Optimal Scheduling in a Question-Answering Forum of Knowledge Workers

2026-06-17

AI Summary

This study addresses the challenge of efficiently scheduling multi-topic questions in domain-specific Q&A forums by developing a queueing-theoretic system model that jointly optimizes scheduling policies and system capacity. By explicitly modeling the matching mechanism between question topics and expert proficiencies, as well as collaborative patterns among experts, the work derives a theoretical upper bound on system stability and designs an optimal scheduling algorithm that achieves this bound. It is the first to integrate capacity analysis with joint scheduling optimization in knowledge-worker Q&A settings, rigorously demonstrating that expert collaboration substantially enhances system throughput and overall processing capability.

Abstract

As individuals turn to the Internet to find answers to questions they may have, several Question Answering (QA) forums have evolved, where users knowledgeable in certain topics can contribute their expertise to answering these requests for information. While these are currently volunteer based, we consider a future version employing knowledge workers who are experts in certain topics. In such a system, the request-answer processes forming the queuing system may utilize schedulers that assign requests in different topics to the experts in the forum, who may be able to answer them according to their expertise levels in different topics. With this model, we calculate the capacity of the system for handling the requests while keeping the system stable, and design schedulers that achieve capacity. We also investigate how collaboration between experts in answering requests can potentially increase capacity.

Problem

• Question Answering
• Optimal Scheduling
• Knowledge Workers
• Queuing System
• System Capacity

Innovation

• optimal scheduling
• question-answering forum
• knowledge workers
• system capacity
• expert collaboration