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Diversity as a Response to User Preference Uncertainty

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Diversity as a Response to User Preference Uncertainty. / Edwards, James Anthony; Leslie, David Stuart.

Statistical Data Science. ed. / Niall Adams; Edwards Cohen. World Scientific, 2018. p. 55-68.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNChapter

Harvard

Edwards, JA & Leslie, DS 2018, Diversity as a Response to User Preference Uncertainty. in N Adams & E Cohen (eds), Statistical Data Science. World Scientific, pp. 55-68. https://doi.org/10.1142/9781786345400_0004

APA

Edwards, J. A., & Leslie, D. S. (2018). Diversity as a Response to User Preference Uncertainty. In N. Adams, & E. Cohen (Eds.), Statistical Data Science (pp. 55-68). World Scientific. https://doi.org/10.1142/9781786345400_0004

Vancouver

Edwards JA, Leslie DS. Diversity as a Response to User Preference Uncertainty. In Adams N, Cohen E, editors, Statistical Data Science. World Scientific. 2018. p. 55-68 https://doi.org/10.1142/9781786345400_0004

Author

Edwards, James Anthony ; Leslie, David Stuart. / Diversity as a Response to User Preference Uncertainty. Statistical Data Science. editor / Niall Adams ; Edwards Cohen. World Scientific, 2018. pp. 55-68

Bibtex

@inbook{1470f5be22244986bb5b3bf7b0610e37,
title = "Diversity as a Response to User Preference Uncertainty",
abstract = "This chapter considers the problem of choosing a set of website elements to present to a user. An often desirable property of such a set is that it is diverse, i.e. the elements are not all similar to one another. Often this is presented as being a separate objective from that of choosing elements that match the user in some way and which are therefore more likely to be clicked. We present a range of simple and intuitive models based on uncertainty about user preferences that show how diversity emerges naturally as a result of seeking to maximise the probability that the user will click on an element. As such we give an argument as to why diversity is desirable which avoids the need for it as a separate objective. The exact model used affects the diversity of sets chosen as well as the likelihood that the user will click on an element.",
keywords = "recommender systems",
author = "Edwards, {James Anthony} and Leslie, {David Stuart}",
year = "2018",
month = "4",
doi = "10.1142/9781786345400_0004",
language = "English",
isbn = "9781786345394",
pages = "55--68",
editor = "Niall Adams and Edwards Cohen",
booktitle = "Statistical Data Science",
publisher = "World Scientific",

}

RIS

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T1 - Diversity as a Response to User Preference Uncertainty

AU - Edwards, James Anthony

AU - Leslie, David Stuart

PY - 2018/4

Y1 - 2018/4

N2 - This chapter considers the problem of choosing a set of website elements to present to a user. An often desirable property of such a set is that it is diverse, i.e. the elements are not all similar to one another. Often this is presented as being a separate objective from that of choosing elements that match the user in some way and which are therefore more likely to be clicked. We present a range of simple and intuitive models based on uncertainty about user preferences that show how diversity emerges naturally as a result of seeking to maximise the probability that the user will click on an element. As such we give an argument as to why diversity is desirable which avoids the need for it as a separate objective. The exact model used affects the diversity of sets chosen as well as the likelihood that the user will click on an element.

AB - This chapter considers the problem of choosing a set of website elements to present to a user. An often desirable property of such a set is that it is diverse, i.e. the elements are not all similar to one another. Often this is presented as being a separate objective from that of choosing elements that match the user in some way and which are therefore more likely to be clicked. We present a range of simple and intuitive models based on uncertainty about user preferences that show how diversity emerges naturally as a result of seeking to maximise the probability that the user will click on an element. As such we give an argument as to why diversity is desirable which avoids the need for it as a separate objective. The exact model used affects the diversity of sets chosen as well as the likelihood that the user will click on an element.

KW - recommender systems

U2 - 10.1142/9781786345400_0004

DO - 10.1142/9781786345400_0004

M3 - Chapter

SN - 9781786345394

SP - 55

EP - 68

BT - Statistical Data Science

A2 - Adams, Niall

A2 - Cohen, Edwards

PB - World Scientific

ER -