Finding shortest keyword covering routes in road networks

Kaffes, Vassilis; Belesiotis, Alexandros; Skoutas, Dimitrios; Skiadopoulos, Spiros

doi:10.1145/3221269.3223038

Cited by 1 publication

(1 citation statement)

References 22 publications

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“…To improve the performance of , the authors further propose an approximate algorithm, namely , which not only returns better approximate guarantees, but is more efficient than . In the literature, a string of other keyword-aware routing problems are studied [37,38,50,87,97,108]. All these works aim at finding optimal routes by considering keywords and other application-specified constraints at the same time.…”

Section: Problem 12 (mentioning

confidence: 99%

Keyword Search on Large Graphs: A Survey

Yang

Zhang

2021

Data Sci. Eng.

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With the prevalence of Internet access and online services, various big graphs are generated in many real applications (e.g., online social networks and knowledge graphs). An important task on analyzing and mining these graphs is keyword search. Essentially, given a graph G and query Q associated with a set of keywords, the keyword search aims to find a substructure (e.g., rooted tree or subgraph) S in G such that nodes in S collectively cover part of or all keywords in Q, and in the meanwhile, S is optimal on some user specified semantics. Keyword search on graphs can be applied in many real-life applications, such as point-of-interests recommendation and web search facility. In spite of the great importance of graph keyword search, we, however, notice that the latest survey on this topic is far out of date. Consequently, there is prompt need to conduct a comprehensive survey in this research direction. Motivated by this, in this survey, we systematically review graph keyword search studies by classifying the existing works into different categories according to the specific problem definition. This survey aims to provide the researchers a comprehensive understanding of existing graph keyword search solutions.

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