Please use this identifier to cite or link to this item:
|Title:||Keyword search in spatial databases: Towards searching by document|
|Authors:||Zhang, D. |
|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|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 13, 2017
checked on Dec 9, 2017
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.