MixedSearch: An Interactive System of Searching for the Best Tuple with Mixed Attributes
Wei-Cheng Wang, Min Xie, Raymond Chi-Wing Wong · 2024
Identifying the best tuples in a large database for users has been a longstanding challenge in database community. Many interactive methods have been proposed to help users search for their best tuples in the database. Specifically, each user undergoes rounds of interaction. In each round, the user is presented with two tuples and is asked to pick the one s/he prefers more. Based on the user feedback, the user preference can be learned implicitly. Eventually, the best tuple w.r.t. the learned user preference is returned. Many systems have been designed for conducting interactive methods. However, they mainly restrict their settings on databases with numerical attributes, neglecting that in reality, databases can also be described by categorical attributes. Although there are some strategies to convert categorical attributes to numerical attributes, the conversion not only incurs poor efficiency, but also requires heavy interactive effort. In light of this, we developed an interactive system, called MixedSearch, and demonstrated that the system could find the best tuples for users in the database described by mixed attributes.