Ranking Database Queries with User Feedback: A Neural Network Approach
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Publisher
Springer Berlin Heidelberg
Link
http://link.springer.com/content/pdf/10.1007/978-3-540-78568-2_31.pdf
Reference8 articles.
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3. Fagin, R.: Combining fuzzy information from multiple systems. In: Proc. of the 15th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems (PODS), Montreal, Canada (1996)
4. Agrawal, R., Wimmers, E.L.: A framework for expressing and combining preferences. In: Proc. of the ACM SIGMOD Conference, Dallas, Texas, USA (2000)
5. Re, C., Dalvi, N., Suciu, D.: Efficient Top-k Query Evaluation on Probabilistic Data. In: Proc. of the 23rd International Conference on Data Engineering (ICDE) (2007)
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Adaptive query relaxation and top-k result ranking over autonomous web databases;Knowledge and Information Systems;2016-08-16
2. Similarity Based Ranking of Query Results from Real Web Databases;2014 Fifth International Conference on Signal and Image Processing;2014-01
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