Extracting the information backbone in online system.
Information overload is a serious problem in modern society and many solutions such as recommender system have been proposed to filter out irrelevant information. In the literature, researchers have been mainly dedicated to improving the recommendation performance (accuracy and diversity) of the alg...
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doaj-351df289b2f74e4cb5295e5abf8be63e2020-11-25T02:22:06ZengPublic Library of Science (PLoS)PLoS ONE1932-62032013-01-0185e6262410.1371/journal.pone.0062624Extracting the information backbone in online system.Qian-Ming ZhangAn ZengMing-Sheng ShangInformation overload is a serious problem in modern society and many solutions such as recommender system have been proposed to filter out irrelevant information. In the literature, researchers have been mainly dedicated to improving the recommendation performance (accuracy and diversity) of the algorithms while they have overlooked the influence of topology of the online user-object bipartite networks. In this paper, we find that some information provided by the bipartite networks is not only redundant but also misleading. With such "less can be more" feature, we design some algorithms to improve the recommendation performance by eliminating some links from the original networks. Moreover, we propose a hybrid method combining the time-aware and topology-aware link removal algorithms to extract the backbone which contains the essential information for the recommender systems. From the practical point of view, our method can improve the performance and reduce the computational time of the recommendation system, thus improving both of their effectiveness and efficiency.http://europepmc.org/articles/PMC3653959?pdf=render |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Qian-Ming Zhang An Zeng Ming-Sheng Shang |
spellingShingle |
Qian-Ming Zhang An Zeng Ming-Sheng Shang Extracting the information backbone in online system. PLoS ONE |
author_facet |
Qian-Ming Zhang An Zeng Ming-Sheng Shang |
author_sort |
Qian-Ming Zhang |
title |
Extracting the information backbone in online system. |
title_short |
Extracting the information backbone in online system. |
title_full |
Extracting the information backbone in online system. |
title_fullStr |
Extracting the information backbone in online system. |
title_full_unstemmed |
Extracting the information backbone in online system. |
title_sort |
extracting the information backbone in online system. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2013-01-01 |
description |
Information overload is a serious problem in modern society and many solutions such as recommender system have been proposed to filter out irrelevant information. In the literature, researchers have been mainly dedicated to improving the recommendation performance (accuracy and diversity) of the algorithms while they have overlooked the influence of topology of the online user-object bipartite networks. In this paper, we find that some information provided by the bipartite networks is not only redundant but also misleading. With such "less can be more" feature, we design some algorithms to improve the recommendation performance by eliminating some links from the original networks. Moreover, we propose a hybrid method combining the time-aware and topology-aware link removal algorithms to extract the backbone which contains the essential information for the recommender systems. From the practical point of view, our method can improve the performance and reduce the computational time of the recommendation system, thus improving both of their effectiveness and efficiency. |
url |
http://europepmc.org/articles/PMC3653959?pdf=render |
work_keys_str_mv |
AT qianmingzhang extractingtheinformationbackboneinonlinesystem AT anzeng extractingtheinformationbackboneinonlinesystem AT mingshengshang extractingtheinformationbackboneinonlinesystem |
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1724863381754609664 |