Monochromatic and bichromatic ranked reverse boolean spatial keyword nearest neighbors search
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- 作者：Pengpeng Zhao ; Hailin Fang ; Victor S. Sheng ; Zhixu Li ; Jiajie Xu ; Jian Wu…
- 关键词：Reverse k nearest neighbor ; Spatial keyword search ; Ranking
- 刊名：World Wide Web
- 出版年：2017
- 出版时间：January 2017
- 年：2017
- 卷：20
- 期：1
- 页码：39-59
- 全文大小：
- 刊物类别：Computer Science
- 刊物主题：Information Systems Applications (incl.Internet); Database Management; Operating Systems;
- 出版者：Springer US
- ISSN：1573-1413
- 卷排序：20
文摘
Recently, Reverse k Nearest Neighbors (RkNN) queries, returning every answer for which the query is one of its k nearest neighbors, have been extensively studied on the database research community. But the RkNN query cannot retrieve spatio-textual objects which are described by their spatial location and a set of keywords. Therefore, researchers proposed a RSTkNN query to find these objects, taking both spatial and textual similarity into consideration. However, the RSTkNN query cannot control the size of answer set and to be sorted according to the degree of influence on the query. In this paper, we propose a new problem Ranked Reverse Boolean Spatial Keyword Nearest Neighbors query called Ranked-RBSKNN query, which considers both spatial similarity and textual relevance, and returns t answers with most degree of influence. We propose a separate index and a hybrid index to process such queries efficiently. Experimental results on different real-world and synthetic datasets show that our approaches achieve better performance.