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
Indexing Relational Database Content Offline for Efficient Keyword-Based Search
IDEAS '05 Proceedings of the 9th International Database Engineering & Application Symposium
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
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
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Keyword search on structured and semi-structured data
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Structure-aware indexing for keyword search in databases
Proceedings of the 18th ACM conference on Information and knowledge management
Keyword search in geospatial database
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
A framework for evaluating database keyword search strategies
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Keyword-based search and exploration on databases
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
Database Keyword Search: A Perspective from Optimization
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 03
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Research on keyword search in database community has achieved a lot of success, and areas of interests have been moved from keyword search in relational databases to various advanced issues such as keyword search in multimedia data and data streams. Yet, many fundamental issues on keyword search in traditional databases remain. One such issue is how to interpret users' information needs behind keywords they provided. A common approach of many prototype systems is to make such interpretation as a designer's choice (such as imposing AND or OR semantics, or a combination), leaving no choice to the users. A much more meaningful approach would be allowing users themselves to specify the required semantics through contextual information. So can we build a system which stays with the simplicity of Keyword search, yet can incorporate the contextual information provided in the user query? In this paper we introduce STRUCT to explore this idea. STRUCT takes English language queries involving intended keywords; we refer to such search as English query search. Instead of resorting on a full-fledged natural language processing, the unneeded words in the queries are discarded. Only the specific contextual information along with the keywords containing database contents will be used to construct SQL queries. The contextual information is used to interpret the meaning of the queries, including the semantics involving AND, OR and NOT. In this paper we describe the architecture of STRUCT, the procedure of English query processing (parsing), the basic idea of the grouping algorithm, SQL query construction and sample results of experiments.