Issue No. 07 - July (2014 vol. 26)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TKDE.2013.85
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.
query processing, graph theory,minimal answers, duplication free, minimal keyword search, graph search, subgraph, query keywords, content node,Keyword search, Steiner trees, Delays, Algorithm design and analysis, Polynomials, Heuristic algorithms, Approximation algorithms,Algorithms for data and knowledge management, Information Technology and Systems, Database Management, Database Applications, Interactive data exploration and discovery, Computing Methodologies, Symbolic and algebraic manipulation, Algorithms,approximation algorithm, Keyword search, graph data, polynomial delay
"Efficient Duplication Free and Minimal Keyword Search in Graphs", IEEE Transactions on Knowledge & Data Engineering, vol. 26, no. , pp. 1657-1669, July 2014, doi:10.1109/TKDE.2013.85