Maximum Rank Query
The top-k query is a common means to shortlist a number of options from a set of alternatives, based on the user's preferences. Typically, these preferences are expressed as a vector of query weights, defined over the options' attributes. The query vector implicitly associates each alterna...
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sg-smu-ink.sis_research-38232016-05-03T08:03:01Z Maximum Rank Query MOURATIDIS, Kyriakos ZHANG, Jilian Hwee Hwa PANG, The top-k query is a common means to shortlist a number of options from a set of alternatives, based on the user's preferences. Typically, these preferences are expressed as a vector of query weights, defined over the options' attributes. The query vector implicitly associates each alternative with a numeric score, and thus imposes a ranking among them. The top-k result includes the k options with the highest scores. In this context, we define the maximum rank query (MaxRank). Given a focal option in a set of alternatives, the MaxRank problem is to compute the highest rank this option may achieve under any possible user preference, and furthermore, to report all the regions in the query vector's domain where that rank is achieved. MaxRank finds application in market impact analysis, customer profiling, targeted advertising, etc. We propose a methodology for MaxRank processing and evaluate it with experiments on real and benchmark synthetic datasets. 2015-09-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/2823 info:doi/10.14778/2824032.2824053 https://ink.library.smu.edu.sg/context/sis_research/article/3823/viewcontent/VLDB15_MaxRank.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Benchmarking Customer profiling Market impacts Maximum rank Query vectors Synthetic datasets Targeted advertising Top-k query User's preferences Computer Sciences Databases and Information Systems |
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Benchmarking Customer profiling Market impacts Maximum rank Query vectors Synthetic datasets Targeted advertising Top-k query User's preferences Computer Sciences Databases and Information Systems MOURATIDIS, Kyriakos ZHANG, Jilian Hwee Hwa PANG, Maximum Rank Query |
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The top-k query is a common means to shortlist a number of options from a set of alternatives, based on the user's preferences. Typically, these preferences are expressed as a vector of query weights, defined over the options' attributes. The query vector implicitly associates each alternative with a numeric score, and thus imposes a ranking among them. The top-k result includes the k options with the highest scores. In this context, we define the maximum rank query (MaxRank). Given a focal option in a set of alternatives, the MaxRank problem is to compute the highest rank this option may achieve under any possible user preference, and furthermore, to report all the regions in the query vector's domain where that rank is achieved. MaxRank finds application in market impact analysis, customer profiling, targeted advertising, etc. We propose a methodology for MaxRank processing and evaluate it with experiments on real and benchmark synthetic datasets. |
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text |
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MOURATIDIS, Kyriakos ZHANG, Jilian Hwee Hwa PANG, |
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MOURATIDIS, Kyriakos ZHANG, Jilian Hwee Hwa PANG, |
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MOURATIDIS, Kyriakos |
title |
Maximum Rank Query |
title_short |
Maximum Rank Query |
title_full |
Maximum Rank Query |
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Maximum Rank Query |
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Maximum Rank Query |
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maximum rank query |
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Institutional Knowledge at Singapore Management University |
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2015 |
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https://ink.library.smu.edu.sg/sis_research/2823 https://ink.library.smu.edu.sg/context/sis_research/article/3823/viewcontent/VLDB15_MaxRank.pdf |
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