Being Happy with the Least: Achieving α-happiness with Minimum Number of Tuples

CategoryPublications 204

Authors: Min Xie, Raymond Chi-Wing Wong, Peng Peng and Vassilis Tsotras

Name of Conference: IEEE International Conference on Data Engineering (ICDE 2020), April 20-24, 2020, Dallas, Texas, USA

Date of Publication: April 20, 2020


When faced with a database containing millions of products, a user may be only interested in a (typically much) smaller representative subset. Various approaches were proposed to create a good representative subset that fits the user’s needs which are expressed in the form of a utility function (e.g., the top-k and diversification query). Recently, a regret minimization query was proposed: it does not require users to provide their utility functions and returns a small set of tuples such that any user’s favorite tuple in this subset is guaranteed to be not much worse than his/her favorite tuple in the whole database. In a sense, this query finds a small set of tuples that makes the user happy (i.e., not regretful) even if s/he gets the best tuple in the selected set but not the best tuple among all tuples in the database. In this paper, we study the min-size version of the regret minimization query; that is, we want to determine the least tuples needed to keep users happy at a given level. We term this problem as the α-happiness query where we quantify the user’s happiness level by a criterion, called the happiness ratio, and guarantee that each user is at least α happy with the set returned (i.e., the happiness ratio is at least α) where α is a real number from 0 to 1. As this is an NP-hard problem, we derive an approximate solution with theoretical guarantee by considering the problem from a geometric perspective. Since in practical scenarios, users are interested in achieving higher happiness levels (i.e., α is closer to 1), we performed extensive experiments for these scenarios, using both real and synthetic datasets. Our evaluations show that our algorithm outperforms the best-known previous approaches in two ways: (i) it answers the α-happiness query by returning fewer tuples to users and, (ii) it answers much faster (up to two orders of magnitude times improvement for large α).

View Full Text

Keywords2020Approximation theory and practiceICDEMin Xie Previous: Next: