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Automatic categorization of query results
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Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
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Proceedings of the 2006 ACM SIGMOD international conference on Management of data
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ACM Transactions on Database Systems (TODS)
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Foundations of preferences in database systems
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Ranking objects based on attribute value correlation
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Exploiting correlation to rank database query results
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Pragmatic correlation analysis for probabilistic ranking over relational data
Expert Systems with Applications: An International Journal
Querying and ranking incomplete twigs in probabilistic XML
World Wide Web
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To deal with the problem of empty or too little answers returned from a Web database in response to a user query, this paper proposes a novel approach to provide relevant and ranked query results. Based on the user original query, we speculate how much the user cares about each specified attribute and assign a corresponding weight to it. This original query is then rewritten as an approximate query by relaxing the query criteria range. The relaxation order of all specified attributes and the relaxed degree on each specified attribute are varied with the attribute weights. For the approximate query results, we generate users' contextual preferences from database workload and use them to create a priori orders of tuples in an off-line preprocessing step. Only a few representative orders are saved, each corresponding to a set of contexts. Then, these orders and associated contexts are used at query time to expeditiously provide ranked answers. Results of a preliminary user study demonstrate that our query relaxation and results ranking methods can capture the user's preferences effectively. The efficiency and effectiveness of our approach is also demonstrated by experimental result.