Efficient association discovery with keyword-based constraints on large graph data

  • Authors:

  • Mo Zhou;Yifan Pan;Yuqing Wu

  • Affiliations:

  • Indiana University, Bloomington, IN, USA;Indiana University, Bloomington, IN, USA;indiana university, Bloomington, IN, USA

  • Venue:
  • Proceedings of the 20th ACM international conference on Information and knowledge management
  • Year:
  • 2011

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Abstract

In many domains, such as social networks and chem-informatics, data can be represented naturally in graph model, with nodes being data entries and edges the relationships between them. We study the application requirements in these domains and find that discovering Constrained Acyclic Paths (CAP) is highly in demand. In this paper, we define the CAP search problem and introduce a set of quantitative metrics for describing keyword-based constraints. We propose a series of algorithms to efficiently evaluate CAP queries on large-scale graph data. Extensive experiments illustrate that our algorithms are both efficient and scalable.