IR-tree is a spatial text index that combines R-tree with an inverted list.
Published in Chapter:
An Interactive Personalized Spatial Keyword Querying Approach
Xiangfu Meng (Liaoning Technical University, China), Lulu Zhao (Liaoning Technical University, China), Xiaoyan Zhang (Liaoning Technical University, China), Pan Li (Liaoning Technical University, China), Zeqi Zhao (Liaoning Technical University, China), and Yue Mao (Liaoning Technical University, China)
Copyright: © 2019
|Pages: 21
DOI: 10.4018/978-1-5225-8446-9.ch010
Abstract
Existing spatial keyword query methods usually evaluate text relevancy according to the frequency of occurrence of query keywords in the text information associated to spatial objects, without considering the degree of preference of users to different query keywords, and without considering semantic relevancy. To deal with the above problems, this chapter proposes an interactive personalized spatial keyword querying approach which is divided into two stages. In the offline processing stage, Gibbs algorithm is adopted to estimate the thematic probability distribution of text information associated to spatial objects, and then an LDA model is used for semantic expansion of spatial data set.