Dimensionality reduction algorithms for improving efficiency of PromoRank: A comparison study

© Springer International Publishing Switzerland 2015. It is often desirable to find markets or sale channels where an object, e.g., a product, person or service, can be recommended efficiently. Since the object may not be highly ranked in the global property space, PromoRank algorithm promotes a giv...

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Main Authors: Metawat Kavilkrue, Pruet Boonma
Format: Book Series
Published: 2018
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Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84931264757&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/54401
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-544012018-09-04T10:15:35Z Dimensionality reduction algorithms for improving efficiency of PromoRank: A comparison study Metawat Kavilkrue Pruet Boonma Computer Science Engineering © Springer International Publishing Switzerland 2015. It is often desirable to find markets or sale channels where an object, e.g., a product, person or service, can be recommended efficiently. Since the object may not be highly ranked in the global property space, PromoRank algorithm promotes a given object by discovering promotive subspace in which the target is top rank. However, the computation complexity of PromoRank is exponential to the dimension of the space. This paper studies the impact of dimensionality reduction algorithms, such as PCA or FA, in order to reduce the dimension size and, as a consequence, improve the performance of PromoRank. This paper evaluate multiple dimensionality reduction algorithms to obtains the understanding about the relationship between properties of data sets and algorithms such that an appropriate algorithm can be selected for a particular data set. The evaluation results show that dimensionality reduction algorithms can improve the performance of PromoRank while maintain an acceptable ranking accuracy. 2018-09-04T10:12:54Z 2018-09-04T10:12:54Z 2015-01-01 Book Series 21945357 2-s2.0-84931264757 10.1007/978-3-319-19024-2_3 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84931264757&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/54401
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Computer Science
Engineering
spellingShingle Computer Science
Engineering
Metawat Kavilkrue
Pruet Boonma
Dimensionality reduction algorithms for improving efficiency of PromoRank: A comparison study
description © Springer International Publishing Switzerland 2015. It is often desirable to find markets or sale channels where an object, e.g., a product, person or service, can be recommended efficiently. Since the object may not be highly ranked in the global property space, PromoRank algorithm promotes a given object by discovering promotive subspace in which the target is top rank. However, the computation complexity of PromoRank is exponential to the dimension of the space. This paper studies the impact of dimensionality reduction algorithms, such as PCA or FA, in order to reduce the dimension size and, as a consequence, improve the performance of PromoRank. This paper evaluate multiple dimensionality reduction algorithms to obtains the understanding about the relationship between properties of data sets and algorithms such that an appropriate algorithm can be selected for a particular data set. The evaluation results show that dimensionality reduction algorithms can improve the performance of PromoRank while maintain an acceptable ranking accuracy.
format Book Series
author Metawat Kavilkrue
Pruet Boonma
author_facet Metawat Kavilkrue
Pruet Boonma
author_sort Metawat Kavilkrue
title Dimensionality reduction algorithms for improving efficiency of PromoRank: A comparison study
title_short Dimensionality reduction algorithms for improving efficiency of PromoRank: A comparison study
title_full Dimensionality reduction algorithms for improving efficiency of PromoRank: A comparison study
title_fullStr Dimensionality reduction algorithms for improving efficiency of PromoRank: A comparison study
title_full_unstemmed Dimensionality reduction algorithms for improving efficiency of PromoRank: A comparison study
title_sort dimensionality reduction algorithms for improving efficiency of promorank: a comparison study
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84931264757&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/54401
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