Semantic-based delivery of OLAP summary tables in wireless environments
Proceedings of the eleventh international conference on Information and knowledge management
Hand-OLAP: A System for Delivering OLAP Services on Handheld Devices
ISADS '03 Proceedings of the The Sixth International Symposium on Autonomous Decentralized Systems (ISADS'03)
Keyword Searching and Browsing in Databases using BANKS
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Distributed caching of multi-dimensional data in mobile environments
Proceedings of the 6th international conference on Mobile data management
Bidirectional expansion for keyword search on graph databases
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Proceedings of the 8th ACM international workshop on Data warehousing and OLAP
Accuracy Control in Compressed Multidimensional Data Cubes for Quality of Answer-based OLAP Tools
SSDBM '06 Proceedings of the 18th International Conference on Scientific and Statistical Database Management
Spark: top-k keyword query in relational databases
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Effective keyword-based selection of relational databases
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
BLINKS: ranked keyword searches on graphs
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Discover: keyword search in relational databases
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
BANKS: browsing and keyword searching in relational databases
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
A graph method for keyword-based selection of the top-K databases
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Keyword proximity search in complex data graphs
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Keyword search on external memory data graphs
Proceedings of the VLDB Endowment
Top-k Exploration of Query Candidates for Efficient Keyword Search on Graph-Shaped (RDF) Data
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Reachability Indexes for Relational Keyword Search
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Progressive Keyword Search in Relational Databases
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Efficient type-ahead search on relational data: a TASTIER approach
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Enabling OLAP in mobile environments via intelligent data cube compression techniques
Journal of Intelligent Information Systems
Delivering Semantics-aware Compressed OLAP Views in Mobile Environments with Hand-OLAP
ICTAI '09 Proceedings of the 2009 21st IEEE International Conference on Tools with Artificial Intelligence
Ten thousand SQLs: parallel keyword queries computing
Proceedings of the VLDB Endowment
Toward scalable keyword search over relational data
Proceedings of the VLDB Endowment
Identifying the most influential data objects with reverse top-k queries
Proceedings of the VLDB Endowment
Proceedings of the VLDB Endowment
EDBT'04 Proceedings of the 2004 international conference on Current Trends in Database Technology
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Keyword search over databases has recently received significant attention. Many solutions and prototypes have been developed. However, due to large memory consumption requirements and unpredictable running time, most of them cannot be applied directly to the situations where memory is limited and quick response is required, such as when performing keyword search over multidimensional databases in mobile devices as part of the OLAP functionalities. In this paper, the authors attack the keyword search problem from a new perspective, and propose a cascading top-k keyword search algorithm, which generates supernodes by a branch and bound method in each step of search instead of computing the Steiner trees as done in many existing approaches. This new algorithm consumes less memory and significantly reduces the response time. Experiments show that the method can achieve high search efficiency compared with the state-of-the-art approaches.