Diversifying search results is an important research topic in retrieval systems in order to satisfy both the various interests of customers and the equal market exposure of providers. There has been a growing attention on diversity-aware research during recent years, accompanied by a proliferation of literature on methods to promote diversity in search and recommendation. However, the diversity-aware studies in retrieval systems lack a systematic organization and are rather fragmented. In this survey, we are the first to propose a unified taxonomy for classifying the metrics and approaches of diversification in both search and recommendation, which are two of the most extensively researched fields of retrieval systems. We begin the survey with a brief discussion of why diversity is important in retrieval systems, followed by a summary of the various diversity concerns in search and recommendation, highlighting their relationship and differences. For the survey's main body, we present a unified taxonomy of diversification metrics and approaches in retrieval systems, from both the search and recommendation perspectives. In the later part of the survey, we discuss the openness research questions of diversity-aware research in search and recommendation in an effort to inspire future innovations and encourage the implementation of diversity in real-world systems.

翻译：检索系统的多样化搜索结果是检索系统的一个重要研究课题,以满足客户的不同利益和提供者的公平市场接触。近年来,对多样化意识研究越来越重视,同时在搜索和建议中,关于促进多样性方法的文献越来越多。然而,检索系统的多样性认知研究缺乏一个系统组织,而且相当分散。在本次调查中,我们首先提出一个统一的分类法,用于在搜索和建议中将多样化的计量标准和方法分类,这是检索系统研究最广泛的两个领域。我们开始调查时,简要讨论了为什么多样性在检索系统中很重要,然后总结了在搜索和建议中的各种多样性关切,强调了它们之间的关系和差异。关于调查的主体,我们从搜索和建议的角度对多样化计量法和检索系统中的方法进行了统一的分类。在调查的后一部分,我们讨论多样性意识研究的开放性研究问题,以激发未来的创新,鼓励在现实世界系统中实施多样性。