Data Structures, Algorithms, and Applications in C++
Data Structures, Algorithms, and Applications in C++
DBXplorer: enabling keyword search over relational databases
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
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
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
Keyword proximity search in complex data graphs
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Reachability Indexes for Relational Keyword Search
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
EDBT'04 Proceedings of the 2004 international conference on Current Trends in Database Technology
DOLAP 2011: overview of the 14th international workshop on data warehousing and olap
Proceedings of the 20th ACM international conference on Information and knowledge management
| Hi-index | 0.00 |
Keyword search over relational 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 situations where memory is limited and quick response is required, such as when performing keyword search over databases in mobile devices as part of the OLAP funtionalities. In this paper, we attack the keyword search problem from a new perspective, and propose a cascading top-k keyword search algorithm, which generates supernodes 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.