Join processing in relational databases
ACM Computing Surveys (CSUR)
Query evaluation techniques for large databases
ACM Computing Surveys (CSUR)
Principles of database query processing for advanced applications
Principles of database query processing for advanced applications
An overview of query optimization in relational systems
PODS '98 Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Using Semi-Joins to Solve Relational Queries
Journal of the ACM (JACM)
Efficient and extensible algorithms for multi query optimization
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
An Intelligent Search Method for Query Optimization by Semijoins
IEEE Transactions on Knowledge and Data Engineering
Including Group-By in Query Optimization
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
DBXplorer: A System for Keyword-Based Search over Relational Databases
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Keyword Searching and Browsing in Databases using BANKS
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
Précis: The Essence of a Query Answer
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Finding and approximating top-k answers in keyword proximity search
Proceedings of the twenty-fifth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Effective keyword search in relational databases
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
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
Efficient exploitation of similar subexpressions for query processing
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
Efficient IR-style keyword search over relational databases
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Objectrank: authority-based keyword search in databases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Précis: from unstructured keywords as queries to structured databases as answers
The VLDB Journal — The International Journal on Very Large Data Bases
Authority-based keyword search in databases
ACM Transactions on Database Systems (TODS)
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
Scalable multi-query optimization for exploratory queries over federated scientific databases
Proceedings of the VLDB Endowment
Keyword search on external memory data graphs
Proceedings of the VLDB Endowment
Querying Communities in Relational Databases
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Fast ELCA computation for keyword queries on XML data
Proceedings of the 13th International Conference on Extending Database Technology
Understanding queries in a search database system
Proceedings of the twenty-ninth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Exploratory keyword search on data graphs
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Developing IITB Smart CampusGIS Grid
Proceedings of the 1st Amrita ACM-W Celebration on Women in Computing in India
Towards a theory of search queries
ACM Transactions on Database Systems (TODS)
A framework for evaluating database keyword search strategies
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Ten thousand SQLs: parallel keyword queries computing
Proceedings of the VLDB Endowment
Toward scalable keyword search over relational data
Proceedings of the VLDB Endowment
A novel keyword search paradigm in relational databases: Object summaries
Data & Knowledge Engineering
Providing built-in keyword search capabilities in RDBMS
The VLDB Journal — The International Journal on Very Large Data Bases
Finding a minimal tree pattern under neighborhood constraints
Proceedings of the thirtieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Keyword search over relational databases: a metadata approach
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Index structures and top-k join algorithms for native keyword search databases
Proceedings of the 20th ACM international conference on Information and knowledge management
Learning to rank results in relational keyword search
Proceedings of the 20th ACM international conference on Information and knowledge management
Skynets: searching for minimum trees in graphs with incomparable edge weights
Proceedings of the 20th ACM international conference on Information and knowledge management
Integrating and querying web databases and documents
Proceedings of the 20th ACM international conference on Information and knowledge management
SODA: generating SQL for business users
Proceedings of the VLDB Endowment
Predicting the effectiveness of keyword queries on databases
Proceedings of the 21st ACM international conference on Information and knowledge management
Extracting minimum-weight tree patterns from a schema with neighborhood constraints
Proceedings of the 16th International Conference on Database Theory
Reverse engineering complex join queries
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Answering Top-k Keyword Queries on Relational Databases
International Journal of Information Retrieval Research
Hi-index | 0.00 |
Keyword search in relational databases (RDBs) has been extensively studied recently. A keyword search (or a keyword query) in RDBs is specified by a set of keywords to explore the interconnected tuple structures in an RDB that cannot be easily identified using SQL on RDBMS. In brief, it finds how the tuples containing the given keywords are connected via sequences of connections (foreign key references) among tuples in an RDB. Such interconnected tuple structures can be found as connected trees up to a certain size, sets of tuples that are reachable from a root tuple within a radius, or even multi-center subgraphs within a radius. In the literature, there are two main approaches. One is to generate a set of relational algebra expressions and evaluate every such expression using SQL on an RDBMS directly or in a middleware on top of an RDBMS indirectly. Due to a large number of relational algebra expressions needed to process, most of the existing works take a middleware approach without fully utilizing RDBMSs. The other is to materialize an RDB as a graph and find the interconnected tuple structures using graph-based algorithms in memory. In this paper we focus on using SQL to compute all the interconnected tuple structures for a given keyword query. We use three types of interconnected tuple structures to achieve that and we control the size of the structures. We show that the current commercial RDBMSs are powerful enough to support such keyword queries in RDBs efficiently without any additional new indexing to be built and maintained. The main idea behind our approach is tuple reduction. In our approach, in the first reduction step, we prune tuples that do not participate in any results using SQL, and in the second join step, we process the relational algebra expressions using SQL over the reduced relations. We conducted extensive experimental studies using two commercial RDBMSs and two large real datasets, and we report the efficiency of our approaches in this paper.