CLC number: TP391
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2020-03-05
Cited: 0
Clicked: 7215
Asieh Ghanbarpour, Khashayar Niknafs, Hassan Naderi. Efficient keyword search over graph-structured data based on minimal covered r-cliques[J]. Frontiers of Information Technology & Electronic Engineering, 2020, 21(3): 448-464.
@article{title="Efficient keyword search over graph-structured data based on minimal covered r-cliques",
author="Asieh Ghanbarpour, Khashayar Niknafs, Hassan Naderi",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="21",
number="3",
pages="448-464",
year="2020",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1800133"
}
%0 Journal Article
%T Efficient keyword search over graph-structured data based on minimal covered r-cliques
%A Asieh Ghanbarpour
%A Khashayar Niknafs
%A Hassan Naderi
%J Frontiers of Information Technology & Electronic Engineering
%V 21
%N 3
%P 448-464
%@ 2095-9184
%D 2020
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1800133
TY - JOUR
T1 - Efficient keyword search over graph-structured data based on minimal covered r-cliques
A1 - Asieh Ghanbarpour
A1 - Khashayar Niknafs
A1 - Hassan Naderi
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 21
IS - 3
SP - 448
EP - 464
%@ 2095-9184
Y1 - 2020
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1800133
Abstract: keyword search is an alternative for structured languages in querying graph-structured data. A result to a keyword query is a connected structure covering all or part of the queried keywords. The textual coverage and structural compactness have been known as the two main properties of a relevant result to a keyword query. Many previous works examined these properties after retrieving all of the candidate results using a ranking function in a comparative manner. However, this needs a time-consuming search process, which is not appropriate for an interactive system in which the user expects results in the least possible time. This problem has been addressed in recent works by confining the shape of results to examine their coverage and compactness during the search. However, these methods still suffer from the existence of redundant nodes in the retrieved results. In this paper, we introduce the semantic of minimal covered r-clique (MCCr) for the results of a keyword query as an extended model of existing definitions. We propose some efficient algorithms to detect the MCCrs of a given query. These algorithms can retrieve a comprehensive set of non-duplicate MCCrs in response to a keyword query. In addition, these algorithms can be executed in a distributive manner, which makes them outstanding in the field of keyword search. We also propose the approximate versions of these algorithms to retrieve the top-k approximate MCCrs in a polynomial delay. It is proved that the approximate algorithms can retrieve results in two-approximation. Extensive experiments on two real-world datasets confirm the efficiency and effectiveness of the proposed algorithms.
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This article has been corrected, see doi:10.1631/FITEE.18e0133
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