On Social-Temporal Group Query with Acquaintance Constraint

TL;DR

This paper introduces the Social-Temporal Group Query with an acquaintance constraint, aiming to efficiently find optimal activity groups and times that satisfy social familiarity and availability criteria, addressing a complex NP-hard problem.

Contribution

It formulates the problem with integer programming, proves its NP-hardness, and proposes two efficient algorithms, SGSelect and STGSelect, with pruning and pivot techniques for scalable solutions.

Findings

Proposed algorithms outperform existing methods in efficiency and scalability.

STGSelect achieves better solution quality than manual coordination.

Experimental results validate the effectiveness of the algorithms.

Abstract

Three essential criteria are important for activity planning, including: (1) finding a group of attendees familiar with the initiator, (2) ensuring each attendee in the group to have tight social relations with most of the members in the group, and (3) selecting an activity period available for all attendees. Therefore, this paper proposes Social-Temporal Group Query to find the activity time and attendees with the minimum total social distance to the initiator. Moreover, this query incorporates an acquaintance constraint to avoid finding a group with mutually unfamiliar attendees. Efficient processing of the social-temporal group query is very challenging. We show that the problem is NP-hard via a proof and formulate the problem with Integer Programming. We then propose two efficient algorithms, SGSelect and STGSelect, which include effective pruning techniques and employ the idea of pivot time slots to substantially reduce the running time, for finding the optimal solutions. Experimental results indicate that the proposed algorithms are much more efficient and scalable. In the comparison of solution quality, we show that STGSelect outperforms the algorithm that represents manual coordination by the initiator.