TY - GEN
T1 - Answering Why-Not Group Spatial Keyword Queries (Extended Abstract)
AU - Zheng, Bolong
AU - Zheng, Kai
AU - Jensen, Christian S.
AU - Hung, Nguyen Quoc Viet
AU - Su, Han
AU - Li, Guohui
AU - Zhou, Xiaofang
PY - 2019
Y1 - 2019
N2 - With the proliferation of geo-textual objects on the web, extensive efforts have been devoted to improving the efficiency of top-k spatial keyword queries in different settings. However, comparatively much less work has been reported on enhancing the quality and usability of such queries. In this context, we propose means of enhancing the usability of a top-k group spatial keyword query, where a group of users aim to find k objects that contain given query keywords and are nearest to the users. Specifically, when users receive the result of such a query, they may find that one or more objects that they expect to be in the result are in fact missing, and they may wonder why. To address this situation, we develop a so-called why-not query that is able to minimally modify the original query into a query that returns the expected, but missing, objects, in addition to other objects. Specifically, we formalize the why-not query in relation to the top-k group spatial keyword query, called the Why-not Group Spatial Keyword Query (WGSK) that is able to provide a group of users with a more satisfactory query result. We propose a three-phase framework for efficiently computing he WGSK. Extensive experiments with real and synthetic data offer evidence that the proposed solution excels over baselines with respect to both effectiveness and efficiency.
AB - With the proliferation of geo-textual objects on the web, extensive efforts have been devoted to improving the efficiency of top-k spatial keyword queries in different settings. However, comparatively much less work has been reported on enhancing the quality and usability of such queries. In this context, we propose means of enhancing the usability of a top-k group spatial keyword query, where a group of users aim to find k objects that contain given query keywords and are nearest to the users. Specifically, when users receive the result of such a query, they may find that one or more objects that they expect to be in the result are in fact missing, and they may wonder why. To address this situation, we develop a so-called why-not query that is able to minimally modify the original query into a query that returns the expected, but missing, objects, in addition to other objects. Specifically, we formalize the why-not query in relation to the top-k group spatial keyword query, called the Why-not Group Spatial Keyword Query (WGSK) that is able to provide a group of users with a more satisfactory query result. We propose a three-phase framework for efficiently computing he WGSK. Extensive experiments with real and synthetic data offer evidence that the proposed solution excels over baselines with respect to both effectiveness and efficiency.
KW - Query processing
KW - Spatial keyword queries
KW - Top k query
KW - Why not
U2 - 10.1109/ICDE.2019.00272
DO - 10.1109/ICDE.2019.00272
M3 - Article in proceeding
SN - 978-1-5386-7475-8
T3 - Proceedings of the International Conference on Data Engineering
SP - 2155
EP - 2156
BT - Proceedings - 2019 IEEE 35th International Conference on Data Engineering, ICDE 2019
PB - IEEE
T2 - 35th IEEE International Conference on Data Engineering, ICDE 2019
Y2 - 8 April 2019 through 11 April 2019
ER -