期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2017
卷号：6
期号：7
页码：13033
DOI：10.15680/IJIRSET.2017.0607094
出版社：S&S Publications
摘要：We design a location-aware keyword query suggestion framework. We propose a weighted keyworddocumentgraph, which captures both the semantic relevance between keyword queries and the spatial distance betweenthe resulting documents and the user location. The graph is browsed in a random-walk-with-restart fashion to select thekeyword queries with the highest scores as suggestions. To make our framework scalable, we propose a partition-basedapproach that outperforms the baseline algorithm by up to an order of magnitude. The appropriateness of ourframework and the performance of the algorithms are evaluated using real data.
