Typically, a specific market (e.g., of hotels, restaurants, laptops, etc.) is represented as a multi-attribute dataset of the available products. The topic of identifying and shortlisting the products of most interest to a user has been well-explored. In contrast, in this work we focus on the dataset, and aim to assess its competitiveness with regard to different possible preferences. We define measures of competitiveness, and represent them in the form of a heat-map in the domain of preferences. Our work finds application in market analysis and in business development. These applications are further enhanced when the competitiveness heat-map is used in tandem with information on user preferences (which can be readily derived by existing methods). Interestingly, our study also finds side-applications with strong practical relevance in the area of multi-objective querying. We propose a suite of algorithms to efficiently produce the heat-map, and conduct case studies and an empirical evaluation to demonstrate the practicality of our work.

通常，特定市场（例如酒店、餐馆、笔记本电脑等）被表示为可用产品的多属性数据集。识别和筛选用户最感兴趣的产品的主题已经得到了充分的探索。相反，在这项工作中，我们专注于数据集，旨在评估其在不同可能偏好方面的竞争力。我们定义竞争力的衡量标准，并在偏好领域以热图的形式表示它们。我们的工作应用于市场分析和业务开发。当竞争力热图与用户偏好信息（可以通过现有方法轻松导出）结合使用时，这些应用程序将得到进一步增强。有趣的是，我们的研究还发现在多目标查询领域具有很强的实际相关性的侧面应用。我们提出了一套算法来有效地生成热图，并进行案例研究和实证评估来证明我们工作的实用性。