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Solving the apparent diversity-accuracy dilemma of recommender systems

Overview of attention for article published in Proceedings of the National Academy of Sciences of the United States of America, February 2010
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

Mentioned by

news
1 news outlet
twitter
3 tweeters
patent
1 patent

Citations

dimensions_citation
586 Dimensions

Readers on

mendeley
501 Mendeley
citeulike
25 CiteULike
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Title
Solving the apparent diversity-accuracy dilemma of recommender systems
Published in
Proceedings of the National Academy of Sciences of the United States of America, February 2010
DOI 10.1073/pnas.1000488107
Pubmed ID
Authors

T. Zhou, Z. Kuscsik, J.-G. Liu, M. Medo, J. R. Wakeling, Y.-C. Zhang

Abstract

Recommender systems use data on past user preferences to predict possible future likes and interests. A key challenge is that while the most useful individual recommendations are to be found among diverse niche objects, the most reliably accurate results are obtained by methods that recommend objects based on user or object similarity. In this paper we introduce a new algorithm specifically to address the challenge of diversity and show how it can be used to resolve this apparent dilemma when combined in an elegant hybrid with an accuracy-focused algorithm. By tuning the hybrid appropriately we are able to obtain, without relying on any semantic or context-specific information, simultaneous gains in both accuracy and diversity of recommendations.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 501 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 12 2%
Brazil 8 2%
China 6 1%
United Kingdom 5 <1%
Spain 4 <1%
Germany 3 <1%
Canada 3 <1%
Japan 2 <1%
Netherlands 2 <1%
Other 12 2%
Unknown 444 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 134 27%
Student > Master 104 21%
Researcher 59 12%
Student > Bachelor 39 8%
Professor > Associate Professor 31 6%
Other 86 17%
Unknown 48 10%
Readers by discipline Count As %
Computer Science 277 55%
Engineering 30 6%
Physics and Astronomy 27 5%
Business, Management and Accounting 25 5%
Social Sciences 17 3%
Other 62 12%
Unknown 63 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 14. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 May 2020.
All research outputs
#1,612,269
of 17,730,520 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#21,604
of 89,781 outputs
Outputs of similar age
#11,052
of 133,064 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#229
of 838 outputs
Altmetric has tracked 17,730,520 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 89,781 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 31.4. This one has done well, scoring higher than 75% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 133,064 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 838 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.