Scalable top-k keyword search in relational databases

Authors:
Yanwei Xu;Jihong Guan;Yoshiharu Ishikawa
Affiliations:
Department of Computer Science and Technology, Tongji University, Shanghai, China;Department of Computer Science and Technology, Tongji University, Shanghai, China;Information Technology Center, Nagoya University, Nagoya-shi, Japan and Graduate School of Information Science, Nagoya University, Nagoya-shi, Japan and National Institute of Informatics, Tokyo, J ...
Venue:
DASFAA'12 Proceedings of the 17th international conference on Database Systems for Advanced Applications - Volume Part II
Year:
2012

Citing 18
Cited 0

DBXplorer: A System for Keyword-Based Search over Relational Databases

ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Bidirectional expansion for keyword search on graph databases

VLDB '05 Proceedings of the 31st international conference on Very large data bases
Spark: top-k keyword query in 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
Keyword search on relational data streams

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
Efficient IR-style keyword search over relational databases

VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
EASE: an effective 3-in-1 keyword search method for unstructured, semi-structured and structured data

Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Progressive Keyword Search in Relational Databases

ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Scalable Keyword Search on Large Data Streams

ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Querying Communities in Relational Databases

ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Effective Top-k Keyword Search in Relational Databases Considering Query Semantics

Advances in Web and Network Technologies, and Information Management
Keyword Search in Databases

Keyword Search in Databases
Efficient continuous top-k keyword search in relational databases

WAIM'10 Proceedings of the 11th international conference on Web-age information management
Keyword search in relational databases

Knowledge and Information Systems
Scalable keyword search on large data streams

The VLDB Journal — The International Journal on Very Large Data Bases
SPARK2: Top-k Keyword Query in Relational Databases

IEEE Transactions on Knowledge and Data Engineering

Quantified Score

Hi-index	0.00

Visualization

Abstract

Keyword search in relational databases has been widely studied in recent years because it does not require users neither to master a certain structured query language nor to know the complex underlying database schemas. There would be a huge number of valid results for a keyword query in a large database. However, only the top 10 or 20 most relevant matches for the keyword query ---according to some definition of "Relevance"--- are generally of interest. In this paper, we propose an efficient method for answering top-k keyword queries over relational databases. The proposed method is built on an existing scheme of keyword search on relational data streams, but incorporates the ranking mechanisms into the query processing methods and makes two improvements to support top-k keyword search in relational databases. Experimental results validate the effectiveness and efficiency of the proposed method.