Opportunities for spatial database research in the context of preference queries

• Main Author: MOURATIDIS, Kyriakos
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2023
• Subjects: Top-�� query; Skyline; Multi-dimensional datasets; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/8450; https://ink.library.smu.edu.sg/context/sis_research/article/9453/viewcontent/LocalRec23_SpatialPref.pdf
• Institution: Singapore Management University

This is the outline of the keynote speech at LocalRec@ACM SIGSPATIAL 2023. The main objective of the talk is to point out opportunities for spatial database researchers in the area of preference-based querying. We will commence with an overview of the standard queries for multi-objective decision making, and demonstrate their direct connection to recommendations and to market analysis. In this context, there is a number of specific decision criteria, and user preferences are represented as vectors with as many dimensions. We will demonstrate how and why this type of preferences are natural to actual applications and practical for the support of real users in their choices and decisions. Next, we will illustrate that the principles which underlie preference-based querying are actually computational geometric in nature and, for the goal of practicality, they enable the use of spatial data management techniques, such as multi-dimensional indices and geometric reasoning for search space reduction (akin to traditional pruning). To showcase the potential of approaching preference querying challenges via spatial database techniques, we will use three recent studies as examples. The talk will conclude with a recap of the potential to apply a skillset typical to SIGSPATIAL attendees to a new domain, that of preference querying.