Continuous Top-k monitoring on document streams
The efficient processing of document streams plays an important role in many information filtering systems. Emerging applications, such as news update filtering and social network notifications, demand presenting end-users with the most relevant content to their preferences. In this work, user prefe...
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sg-smu-ink.sis_research-46452020-01-21T08:49:43Z Continuous Top-k monitoring on document streams U, Leong Hou ZHANG, Junjie MOURATIDIS, Kyriakos LI, Ye The efficient processing of document streams plays an important role in many information filtering systems. Emerging applications, such as news update filtering and social network notifications, demand presenting end-users with the most relevant content to their preferences. In this work, user preferences are indicated by a set of keywords. A central server monitors the document stream and continuously reports to each user the top-k documents that are most relevant to her keywords. Our objective is to support large numbers of users and high stream rates, while refreshing the top-k results almost instantaneously. Our solution abandons the traditional frequency-ordered indexing approach. Instead, it follows an identifier-ordering paradigm that suits better the nature of the problem. When complemented with a novel, locally adaptive technique, our method offers (i) proven optimality w.r.t. the number of considered queries per stream event, and (ii) an order of magnitude shorter response time (i.e., time to refresh the query results) than the current state-of-the-art. 2017-05-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/3643 info:doi/10.1109/TKDE.2017.2657622 https://ink.library.smu.edu.sg/context/sis_research/article/4645/viewcontent/TKDE17_MRIO__1_.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 Top-k query Continuous query Document stream Databases and Information Systems Numerical Analysis and Scientific Computing |
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Top-k query Continuous query Document stream Databases and Information Systems Numerical Analysis and Scientific Computing U, Leong Hou ZHANG, Junjie MOURATIDIS, Kyriakos LI, Ye Continuous Top-k monitoring on document streams |
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The efficient processing of document streams plays an important role in many information filtering systems. Emerging applications, such as news update filtering and social network notifications, demand presenting end-users with the most relevant content to their preferences. In this work, user preferences are indicated by a set of keywords. A central server monitors the document stream and continuously reports to each user the top-k documents that are most relevant to her keywords. Our objective is to support large numbers of users and high stream rates, while refreshing the top-k results almost instantaneously. Our solution abandons the traditional frequency-ordered indexing approach. Instead, it follows an identifier-ordering paradigm that suits better the nature of the problem. When complemented with a novel, locally adaptive technique, our method offers (i) proven optimality w.r.t. the number of considered queries per stream event, and (ii) an order of magnitude shorter response time (i.e., time to refresh the query results) than the current state-of-the-art. |
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text |
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U, Leong Hou ZHANG, Junjie MOURATIDIS, Kyriakos LI, Ye |
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U, Leong Hou ZHANG, Junjie MOURATIDIS, Kyriakos LI, Ye |
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U, Leong Hou |
title |
Continuous Top-k monitoring on document streams |
title_short |
Continuous Top-k monitoring on document streams |
title_full |
Continuous Top-k monitoring on document streams |
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Continuous Top-k monitoring on document streams |
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Continuous Top-k monitoring on document streams |
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continuous top-k monitoring on document streams |
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Institutional Knowledge at Singapore Management University |
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2017 |
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https://ink.library.smu.edu.sg/sis_research/3643 https://ink.library.smu.edu.sg/context/sis_research/article/4645/viewcontent/TKDE17_MRIO__1_.pdf |
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