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Aggregate Nearest Keyword Search in Spatial Databases

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4 Author(s)
Zhicheng Li ; Huazhong Univ. of Sci. & Technol., Wuhan, China ; Hu Xu ; Yansheng Lu ; Ailing Qian

Given a set of spatial points $D$ containing keywords information, a set of query objects Q and m query keywords, a top-k aggregate nearest keyword (ANK) query retrieves k objects from Q with the minimum sum of distances to its nearest points in D such that each nearest point matches at least one of query keywords. For example, consider there is a spatial database D which manages facilities (e.g., school, restaurants, hospital, etc.) represented by sets of keywords. A user may want to rank a set of locations with respect to the sum of distances to nearest interested facilities. For processing this query, several algorithms are proposed using IR2-Tree as index structure. Experiments on real data sets indicate that our approach is scalable and efficient in reducing query response time.

Published in:

Web Conference (APWEB), 2010 12th International Asia-Pacific

Date of Conference:

6-8 April 2010