Building and Maintaining Halls of Fame over a Database
Foteini Alvanaki, Sebastian Michel, Aleksandar Stupar

TL;DR
This paper presents a method for automatically detecting and ranking significant changes in Hall of Fame rankings derived from database data, with a prototype system evaluated on basketball statistics.
Contribution
It introduces a novel approach to identifying and ranking noteworthy events in database-driven Hall of Fame rankings using SQL queries and change detection techniques.
Findings
Effective detection of ranking changes in real-world data
A prototype system using triggers and middleware
Successful evaluation on basketball statistics dataset
Abstract
Halls of Fame are fascinating constructs. They represent the elite of an often very large amount of entities---persons, companies, products, countries etc. Beyond their practical use as static rankings, changes to them are particularly interesting---for decision making processes, as input to common media or novel narrative science applications, or simply consumed by users. In this work, we aim at detecting events that can be characterized by changes to a Hall of Fame ranking in an automated way. We describe how the schema and data of a database can be used to generate Halls of Fame. In this database scenario, by Hall of Fame we refer to distinguished tuples; entities, whose characteristics set them apart from the majority. We define every Hall of Fame as one specific instance of an SQL query, such that a change in its result is considered a noteworthy event. Identified changes (i.e.,…
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Taxonomy
TopicsData Management and Algorithms · Advanced Database Systems and Queries · Algorithms and Data Compression
