RT Journal Article
JF IEEE Transactions on Knowledge & Data Engineering
YR 2014
VO 26
IS 7
SP 1657
TI Efficient Duplication Free and Minimal Keyword Search in Graphs
A1 Mehdi Kargar,
A1 Aijun An,
A1 Xiaohui Yu,
K1 query processing
K1 graph theory
K1 minimal answers
K1 duplication free
K1 minimal keyword search
K1 graph search
K1 subgraph
K1 query keywords
K1 content node
K1 Keyword search
K1 Steiner trees
K1 Delays
K1 Algorithm design and analysis
K1 Polynomials
K1 Heuristic algorithms
K1 Approximation algorithms
K1 Algorithms for data and knowledge management
K1 Information Technology and Systems
K1 Database Management
K1 Database Applications
K1 Interactive data exploration and discovery
K1 Computing Methodologies
K1 Symbolic and algebraic manipulation
K1 Algorithms
K1 approximation algorithm
K1 Keyword search
K1 graph data
K1 polynomial delay
AB Keyword search over a graph searches for a subgraph that contains a set of query keywords. A problem with most existing keyword search methods is that they may produce duplicate answers that contain the same set of content nodes (i.e., nodes containing a query keyword) although these nodes may be connected differently in different answers. Thus, users may be presented with many similar answers with trivial differences. In addition, some of the nodes in an answer may contain query keywords that are all covered by other nodes in the answer. Removing these nodes does not change the coverage of the answer but can make the answer more compact. The answers in which each content node contains at least one unique query keyword are called minimal answers in this paper. We define the problem of finding duplication-free and minimal answers, and propose algorithms for finding such answers efficiently. Extensive performance studies using two large real data sets confirm the efficiency and effectiveness of the proposed methods.
PB IEEE Computer Society, [URL:http://www.computer.org]
SN 1041-4347
LA English
DO 10.1109/TKDE.2013.85
LK http://doi.ieeecomputersociety.org/10.1109/TKDE.2013.85