Abstract
Spatial keyword search is a useful technique to enable users find the spatial web object they prefer. Since they objects spatially close to the query point may not fulfill all query objectives, collective spatial keyword query aims to retrieve a group of objects that can cover all required query keywords while properly located in spatial. However in some cases, the querying may be subject to several people in different locations together, and the returned group of objects should not only cover all of their objectives, but also optimal regarding to all of the related people. To this end, this paper studies the problem of multiple query point based collective spatial keyword querying (MCSKQ). Two novel algorithms, HCQ and BCQ, are proposed to support efficient collective query processing w.r.t. multiple query points. The experimental results and related analysis show that MCSKQ has good efficiency and accuracy performance.
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Li, Y., Wang, Z., Chen, J., Wang, F., Xu, J. (2019). Multiple Query Point Based Collective Spatial Keyword Querying. In: Li, J., Wang, S., Qin, S., Li, X., Wang, S. (eds) Advanced Data Mining and Applications. ADMA 2019. Lecture Notes in Computer Science(), vol 11888. Springer, Cham. https://doi.org/10.1007/978-3-030-35231-8_5
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