Scheduled System Maintenance:
On Wednesday, July 29th, IEEE Xplore will undergo scheduled maintenance from 7:00-9:00 AM ET (11:00-13:00 UTC). During this time there may be intermittent impact on performance. We apologize for any inconvenience.
By Topic

An efficient approach for approximate keyword query in geographic information system

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Zhijun Wang ; Glorious Sun Sch. of Bus. & Manage., Donghua Univ., Shanghai, China ; Ming Du ; Xiujin Shi ; Jiajin Le

Spatial-Keyword (SK) queries, which are queries on spatial objects associated with textual attributes, have received significant attention in geographic information system (GIS) recently. Many hybrid index structures have been proposed to answer SK queries. To the best of our knowledge, however, few of them are adequate to handle approximate keyword matching in space database efficiently. This means they are not error-tolerant for users. In this paper we propose a novel approach for Approximate SK queries-ASK queries, whose motivation is to find the spatial objects with their textual attributes similar to the user-specified keyword and their locations satisfied with the regional requirement. To do so, a 3-level hybrid index structure is introduced. This structure combines R*-tree and inverted lists with the q-grams of the keywords of the objects. R*-tree partitions the objects as well as regional q-grams, which are the qgrams of the keywords of the objects assigned to a leaf node of the R*-tree. Moreover, the regional q-grams are index by inverted lists whose entries are the objects associated with the regional q-gram. Based on the 3-level structure, we give an algorithm for ASK query. Experiments show our approach is efficient because of the reduction of search space.

Published in:

Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on  (Volume:3 )

Date of Conference:

20-22 Nov. 2009