Finding top-k min-cost connected trees in databases

Publication Type:
Conference Proceeding
Citation:
Proceedings - International Conference on Data Engineering, 2007, pp. 836 - 845
Issue Date:
2007-09-24
Full metadata record
Files in This Item:
Filename Description Size
Thumbnail2013002366OK.pdf396.52 kB
Adobe PDF
It widely realized that the integration of database and information retrieval techniques will provide users with a wide range of high quality services. In this paper, we study processing an l-keyword query, p1, p2, ⋯, p1, against a relational database which can be modeled as a weighted graph, G(V, E). Here V is a set of nodes (tuples) and E is a set of edges representing foreign key references between tuples. Let Vi⊆7 V be a set of nodes that contain the keyword pi. We study finding top-k minimum cost connected trees that contain at least one node in every subset Vi, and denote our problem as GST-k When k = 1, it is known as a minimum cost group Steiner tree problem which is NP-Complete. We observe that the number of keywords, l, is small, and propose a novel parameterized solution, with l as a parameter, to find the optimal GST-1, in time complexity O(3ln + 2l((l + log n)n + m)), where n and m are the numbers of nodes and edges in graph G. Our solution can handle graphs with a large number of nodes. Our GST-1 solution can be easily extended to support GST-k, which outperforms the existing GST-k solutions over both weighted undirected/directed graphs. We conducted extensive experimental studies, and report our finding. © 2007 IEEE.
Please use this identifier to cite or link to this item: