User Simulation for Evaluating Information Access Systems

TL;DR

This paper reviews user simulation techniques for evaluating information access systems like search engines and conversational assistants, addressing the challenge of assessing system effectiveness amid diverse user behaviors.

Contribution

It systematically surveys research progress in user simulation frameworks, models, and algorithms for evaluating various information access systems, and discusses future research directions.

Findings

Comprehensive review of user simulation methods for evaluation.

Connections established with machine learning, dialogue systems, and economics.

Discussion of future research directions beyond current evaluation methods.

Abstract

Information access systems, such as search engines, recommender systems, and conversational assistants, have become integral to our daily lives as they help us satisfy our information needs. However, evaluating the effectiveness of these systems presents a long-standing and complex scientific challenge. This challenge is rooted in the difficulty of assessing a system's overall effectiveness in assisting users to complete tasks through interactive support, and further exacerbated by the substantial variation in user behaviour and preferences. To address this challenge, user simulation emerges as a promising solution. This book focuses on providing a thorough understanding of user simulation techniques designed specifically for evaluation purposes. We begin with a background of information access system evaluation and explore the diverse applications of user simulation. Subsequently, we systematically review the major research progress in user simulation, covering both general frameworks for designing user simulators, utilizing user simulation for evaluation, and specific models and algorithms for simulating user interactions with search engines, recommender systems, and conversational assistants. Realizing that user simulation is an interdisciplinary research topic, whenever possible, we attempt to establish connections with related fields, including machine learning, dialogue systems, user modeling, and economics. We end the book with a detailed discussion of important future research directions, many of which extend beyond the evaluation of information access systems and are expected to have broader impact on how to evaluate interactive intelligent systems in general.