2012/09/10 by Sutanay Choudhury, Choudhury, Sutanay, Lawrence B. Holder +7
Computer Science · #Data Management and Algorithms #Databases (cs.DB) #FOS: Computer and information sciences #Graph Theory and Algorithms #Social and Information Networks (cs.SI) #Web Data Mining and Analysis
paper · pdf · doi:10.48550/arxiv.1209.2178
openalex publication_date 2012/09/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Acting on time-critical events by processing ever growing social media or news streams is a major technical challenge. Many of these data sources can be modeled as multi-relational graphs. Continuous queries or techniques to search for rare events that typically arise in monitoring applications have been studied extensively for relational databases. This work is dedicated to answer the question that emerges naturally: how can we efficiently execute a continuous query on a dynamic graph? This paper presents an exact subgraph search algorithm that exploits the temporal characteristics of representative queries for online news or social media monitoring. The algorithm is based on a novel data structure called the Subgraph Join Tree (SJ-Tree) that leverages the structural and semantic characteristics of the underlying multi-relational graph. The paper concludes with extensive experimentation on several real-world datasets that demonstrates the validity of this approach.