Involving users in early phases of software development has become a common strategy as it enables developers to consider user needs from the beginning. Once a system is in production, new opportunities to observe, evaluate and learn from users emerge as more information becomes available. Gathering information from users to continuously evaluate their behavior is a common practice for commercial software, while the Cranfield paradigm remains the preferred option for Information Retrieval (IR) and recommendation systems in the academic world. Here we introduce the Infrastructures for Living Labs STELLA project which aims to create an evaluation infrastructure allowing experimental systems to run along production web-based academic search systems with real users. STELLA combines user interactions and log files analyses to enable large-scale A/B experiments for academic search.
翻译:使用户参与软件开发早期阶段已成为一项共同战略,因为它使开发者能够从一开始就考虑用户的需要。一旦一个系统投入生产,随着更多信息的出现,用户便有新的观察、评价和学习机会。从用户收集信息以不断评价其行为是商业软件的常见做法,而Cranfield模式仍然是学术界信息检索和建议系统的首选选择。这里我们介绍“生活实验室基础设施STELLA”项目,该项目旨在建立一个评价基础设施,使实验系统能够与实际用户一起运行基于网络的生产学术搜索系统。STELLA将用户互动和日志文件分析结合起来,以便能够进行大规模的A/B学术搜索实验。