Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICDE.2009.77
Title: Keyword search in spatial databases: Towards searching by document
Authors: Zhang, D. 
Chee, Y.M.
Mondal, A.
Tung, A.K.H. 
Kitsuregawa, M.
Issue Date: 2009
Source: Zhang, D.,Chee, Y.M.,Mondal, A.,Tung, A.K.H.,Kitsuregawa, M. (2009). Keyword search in spatial databases: Towards searching by document. Proceedings - International Conference on Data Engineering : 688-699. ScholarBank@NUS Repository. https://doi.org/10.1109/ICDE.2009.77
Abstract: This work addresses a novel spatial keyword query called the m-closest keywords (mCK) query. Given a database of spatial objects, each tuple is associated with some descriptive information represented in the form of keywords. The mCK query aims to find the spatially closest tuples which match m user-specified keywords. Given a set of keywords from a document, mCK query can be very useful in geotagging the document by comparing the keywords to other geotagged documents in a database. To answer mCK queries efficiently, we introduce a new index called the bR*-tree, which is an extension of the R*-tree. Based on bR*-tree, we exploit a priori-based search strategies to effectively reduce the search space. We also propose two monotone constraints, namely the distance mutex and keyword mutex, as our a priori properties to facilitate effective pruning. Our performance study demonstrates that our search strategy is indeed efficient in reducing query response time and demonstrates remarkable scalability in terms of the number of query keywords which is essential for our main application of searching by document. © 2009 IEEE.
Source Title: Proceedings - International Conference on Data Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/40769
ISBN: 9780769535456
ISSN: 10844627
DOI: 10.1109/ICDE.2009.77
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

162
checked on Dec 13, 2017

Page view(s)

61
checked on Dec 9, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.