DBXplorer: enabling keyword search over relational databases
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
XRANK: ranked keyword search over XML documents
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Keyword Proximity Search in XML Trees
IEEE Transactions on Knowledge and Data Engineering
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
Effective keyword-based selection of relational databases
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
Towards keyword-driven analytical processing
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
Unsupervised query segmentation using generative language models and wikipedia
Proceedings of the 17th international conference on World Wide Web
A graph method for keyword-based selection of the top-K databases
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Proceedings of the VLDB Endowment
Keyword Search in Spatial Databases: Towards Searching by Document
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Query segmentation using conditional random fields
Proceedings of the First International Workshop on Keyword Search on Structured Data
Probabilistic query rewriting for efficient and effective keyword search on graph data
Proceedings of the VLDB Endowment
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Keyword queries over databases are often dirty with some irrelevant or incorrect words, which has a negative impact on the efficiency and accuracy of keyword query processing. In addition, the keywords in a given query often form natural segments. For example, the query "Tom Hanks Green Mile" can be considered as consisting of two segments, "Tom Hanks" and "Green Mile".The goal of keyword query cleaning is to identify the optimal segmentation of the query, with semantic linkage and spelling corrections also considered.Query cleaning not only helps obtaining queries of higher quality, but also improves the efficiency of query processing by reducing the search space. The seminal work along this direction by Pu and Yu does not consider the role of query logs in performing query cleaning. Query logs contain user-issued queries together with the segmentations chosen by the user, and thus convey important information that reflects user preferences. In this paper, we explore the use of query logs to improve the quality of keyword query cleaning. We propose two methods to adapt the scoring functions of segmentations to account for information gathered from the logs. The effectiveness of our approach are verified with extensive experiments conducted on real data sets.