Object Selection under Team Context

TL;DR

This paper explores integrating team context into database queries to improve team-based data retrieval, proposing algorithms that enhance efficiency without sacrificing accuracy, supported by extensive empirical evaluation.

Contribution

It introduces novel algorithms for team context-aware database querying, emphasizing computational efficiency and effectiveness in team-oriented data retrieval.

Findings

Optimized algorithm matches naive results with better efficiency

Empirical results demonstrate improved query performance

Team context integration enhances database query relevance

Abstract

Context-aware database has drawn increasing attention from both industry and academia recently by taking users' current situation and environment into consideration. However, most of the literature focus on individual context, overlooking the team users. In this paper, we investigate how to integrate team context into database query process to help the users' get top-ranked database tuples and make the team more competitive. We introduce naive and optimized query algorithm to select the suitable records and show that they output the same results while the latter is more computational efficient. Extensive empirical studies are conducted to evaluate the query approaches and demonstrate their effectiveness and efficiency.