Hybrid index structures for location-based web search
By Yinghua Zhou, Xing Xie, Chuang Wang, Yuchang Gong, Wei-Ying Ma. International Conference on Information and Knowledge Management, 2005
311 citations recorded by the source corpus.
Subfields: Geography, Planning and Development, Information Systems, Signal Processing
View Paper: https://www.semanticscholar.org/paper/01ad75f24ba1da988b0faaba738bb1504ef565c1
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Geography, Planning and Development
- Gao Cong
- Christian S. Jensen
- Dingming Wu
- Yen-Yu Chen
- Wang-Chien Lee
- Torsten Suel
- Dik Lun Lee
- Alexander Markowetz
In Information Systems
- Gao Cong
- Christian S. Jensen
- Dingming Wu
- Bijit Hore
- Sharad Mehrotra
- Wang-Chien Lee
- Torsten Suel
- Dik Lun Lee
In Signal Processing
- Gao Cong
- Christian S. Jensen
- Dingming Wu
- Lisi Chen
- Yen-Yu Chen
- Sharad Mehrotra
- Wang-Chien Lee
- Torsten Suel
Citations in the corpus
- Efficient query processing in geographic web search engines (2006, methodology): “Very recently, and concurrent with our work, Zhou et al. [46] have proposed algorithms for geographic query processing under a setup similar to ours.”
- Processing Spatial-Keyword (SK) Queries in Geographic Information Retrieval (GIR) Systems (2007, methodology): “[3, 22] also discuss variants of this approach.”
- Keyword Search on Spatial Databases (2008, background): “Christodoulakis [FC84, FC85 ,Fal85] asamethod toefficiently search acollection oftextdocuments.”
- IR-Tree: An Efficient Index for Geographic Document Search (2011, methodology): “In this paper, we propose an efficient index, calledIR-tree, that together with a top-k document search algorithm facilitates four major tasks in document searches, namely, spatial filtering, textual filtering, relevance computation and document ranking in a fully integrated manner.”
- Spatial Keyword Query Processing: An Experimental Evaluation (2013, methodology): “In early work [26], the R-tree based indices loosely combine the R-tree and inverted files to organize the spatial and text data separately.”