@article{MAKHILLAJIT201413115894,
    title = {Efficient Cluster Based Processing of Joint Top-K Spatial Keyword Queries},
    journal = {Asian Journal of Information Technology},
    volume = {13},
    number = {11},
    pages = {678-683},
    year = {2014},
    issn = {1682-3915},
    doi = {ajit.2014.678.683},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2014.678.683},
    author = {A. Sasi and},
    keywords = {Clustering,association rules,pruning,top-k query,spatial databases,textual databases},
    abstract = {Due to the large number of spatial relations in databases, much research focuses on developing
algorithms to efficiently extract the spatial query processing. In this study, the problem is defined for top-k
spatial keyword search which retrieves the top-k spatial objects that are most relevant to query in terms of joint
spatial and textual relevance. The proposed work aims to provide the solution by introducing a complete
geospatial knowledge discovery framework for the detection of spatial patterns with pruning. These spatial
patterns will not contain any query keywords. A novel approach and indexing structure is proposed for the
joint processing of top-k spatial keyword queries using cluster based association rule mining. If the load is
heavy, then the joint processing keyword query is used to improve the robustness of the proposed work.}
    }