The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Fast evaluation of structured queries for information retrieval
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Distance browsing in spatial databases
ACM Transactions on Database Systems (TODS)
The onion technique: indexing for linear optimization queries
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Optimal aggregation algorithms for middleware
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Modern Information Retrieval
Impact transformation: effective and efficient web retrieval
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
An Enhanced Technique for k-Nearest Neighbor Queries with Non-Spatial Selection Predicates
Multimedia Tools and Applications
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Spatial Join Processing Using Corner Transformation
IEEE Transactions on Knowledge and Data Engineering
The R+-Tree: A Dynamic Index for Multi-Dimensional Objects
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
The Multilevel Grid File - A Dynamic Hierarchical Multidimensional File Structure
Proceedings of the Second International Symposium on Database Systems for Advanced Applications
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Odysseus: A High-Performance ORDBMS Tightly-Coupled with IR Features
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Indexing and ranking in Geo-IR systems
Proceedings of the 2005 workshop on Geographic information retrieval
Hybrid index structures for location-based web search
Proceedings of the 14th ACM international conference on Information and knowledge management
Inverted files for text search engines
ACM Computing Surveys (CSUR)
Efficient query processing in geographic web search engines
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Processing Spatial-Keyword (SK) Queries in Geographic Information Retrieval (GIR) Systems
SSDBM '07 Proceedings of the 19th International Conference on Scientific and Statistical Database Management
Optimized query execution in large search engines with global page ordering
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
A survey of top-k query processing techniques in relational database systems
ACM Computing Surveys (CSUR)
BEIRA: An Area-based User Interface for Map Services
World Wide Web
Keyword Search on Spatial Databases
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Efficient retrieval of the top-k most relevant spatial web objects
Proceedings of the VLDB Endowment
IR-Tree: An Efficient Index for Geographic Document Search
IEEE Transactions on Knowledge and Data Engineering
Efficient processing of top-k spatial keyword queries
SSTD'11 Proceedings of the 12th international conference on Advances in spatial and temporal databases
World Wide Web
Spatio-textual indexing for geographical search on the web
SSTD'05 Proceedings of the 9th international conference on Advances in Spatial and Temporal Databases
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A top-k spatial keyword query returns k objects having the highest (or lowest) scores with regard to spatial proximity as well as text relevancy. Approaches for answering top-k spatial keyword queries can be classified into two categories: the separate index approach and the hybrid index approach. The separate index approach maintains the spatial index and the text index independently and can accommodate new data types. However, it is difficult to support top-k pruning and merging efficiently at the same time since it requires two different orders for clustering the objects: the first based on scores for top-k pruning and the second based on object IDs for efficient merging. In this paper, we propose a new separate index method called Rank-Aware Separate Index Method (RASIM) for top-k spatial keyword queries. RASIM supports both top-k pruning and efficient merging at the same time by clustering each separate index in two different orders through the partitioning technique. Specifically, RASIM partitions the set of objects in each index into rank-aware (RA) groups that contain the objects with similar scores and applies the first order to these groups according to their scores and the second order to the objects within each group according to their object IDs. Based on the RA groups, we propose two query processing algorithms: (i) External Threshold Algorithm (External TA) that supports top-k pruning in the unit of RA groups and (ii) Generalized External TA that enhances the performance of External TA by exploiting special properties of the RA groups. RASIM is the first research work that supports top-k pruning based on the separate index approach. Naturally, it keeps the advantages of the separate index approach. In addition, in terms of storage and query processing time, RASIM is more efficient than the IR-tree method, which is the prevailing method to support top-k pruning to date and is based on the hybrid index approach. Experimental results show that, compared with the IR-tree method, the index size of RASIM is reduced by up to 1.85 times, and the query performance is improved by up to 3.22 times.