Measuring user preference changes in digital libraries

Yang Sun; Huajing Li; Isaac G. Councill; Wang Chien Lee; C. Lee Giles

doi:10.1145/1458082.1458353

Measuring user preference changes in digital libraries

Yang Sun, Huajing Li, Isaac G. Councill, Wang Chien Lee, C. Lee Giles

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

Abstract

Much research has been conducted using web access logs to study implicit user feedback and infer user preferences from clickstreams. However, little research measures the changes of user preferences of ranking documents over time. We present a study that measures the changes of user preferences based on an analysis of access logs of a large scale digital library over one year. A metric based on the accuracy of predicting future user actions is proposed. The results show that although user preferences change over time, the majority of user actions should be predictable from previous browsing behavior in the digital library.

Original language	English (US)
Title of host publication	Proceedings of the 17th ACM Conference on Information and Knowledge Management, CIKM'08
Pages	1497-1498
Number of pages	2
DOIs	https://doi.org/10.1145/1458082.1458353
State	Published - 2008
Event	17th ACM Conference on Information and Knowledge Management, CIKM'08 - Napa Valley, CA, United States Duration: Oct 26 2008 → Oct 30 2008

Publication series

Name	International Conference on Information and Knowledge Management, Proceedings

Other

Other	17th ACM Conference on Information and Knowledge Management, CIKM'08
Country/Territory	United States
City	Napa Valley, CA
Period	10/26/08 → 10/30/08

All Science Journal Classification (ASJC) codes

General Business, Management and Accounting
General Decision Sciences

Access to Document

10.1145/1458082.1458353

Cite this

@inproceedings{f19ae893d2334db587c736229629f27a,

title = "Measuring user preference changes in digital libraries",

abstract = "Much research has been conducted using web access logs to study implicit user feedback and infer user preferences from clickstreams. However, little research measures the changes of user preferences of ranking documents over time. We present a study that measures the changes of user preferences based on an analysis of access logs of a large scale digital library over one year. A metric based on the accuracy of predicting future user actions is proposed. The results show that although user preferences change over time, the majority of user actions should be predictable from previous browsing behavior in the digital library.",

author = "Yang Sun and Huajing Li and Councill, {Isaac G.} and Lee, {Wang Chien} and Giles, {C. Lee}",

year = "2008",

doi = "10.1145/1458082.1458353",

language = "English (US)",

isbn = "9781595939913",

series = "International Conference on Information and Knowledge Management, Proceedings",

pages = "1497--1498",

booktitle = "Proceedings of the 17th ACM Conference on Information and Knowledge Management, CIKM'08",

}

Sun, Y, Li, H, Councill, IG, Lee, WC & Giles, CL 2008, Measuring user preference changes in digital libraries. in Proceedings of the 17th ACM Conference on Information and Knowledge Management, CIKM'08. International Conference on Information and Knowledge Management, Proceedings, pp. 1497-1498, 17th ACM Conference on Information and Knowledge Management, CIKM'08, Napa Valley, CA, United States, 10/26/08. https://doi.org/10.1145/1458082.1458353

Measuring user preference changes in digital libraries. / Sun, Yang; Li, Huajing; Councill, Isaac G. et al.
Proceedings of the 17th ACM Conference on Information and Knowledge Management, CIKM'08. 2008. p. 1497-1498 (International Conference on Information and Knowledge Management, Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Measuring user preference changes in digital libraries

AU - Sun, Yang

AU - Li, Huajing

AU - Councill, Isaac G.

AU - Lee, Wang Chien

AU - Giles, C. Lee

PY - 2008

Y1 - 2008

N2 - Much research has been conducted using web access logs to study implicit user feedback and infer user preferences from clickstreams. However, little research measures the changes of user preferences of ranking documents over time. We present a study that measures the changes of user preferences based on an analysis of access logs of a large scale digital library over one year. A metric based on the accuracy of predicting future user actions is proposed. The results show that although user preferences change over time, the majority of user actions should be predictable from previous browsing behavior in the digital library.

AB - Much research has been conducted using web access logs to study implicit user feedback and infer user preferences from clickstreams. However, little research measures the changes of user preferences of ranking documents over time. We present a study that measures the changes of user preferences based on an analysis of access logs of a large scale digital library over one year. A metric based on the accuracy of predicting future user actions is proposed. The results show that although user preferences change over time, the majority of user actions should be predictable from previous browsing behavior in the digital library.

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U2 - 10.1145/1458082.1458353

DO - 10.1145/1458082.1458353

M3 - Conference contribution

AN - SCOPUS:70349260708

SN - 9781595939913

T3 - International Conference on Information and Knowledge Management, Proceedings

SP - 1497

EP - 1498

BT - Proceedings of the 17th ACM Conference on Information and Knowledge Management, CIKM'08

T2 - 17th ACM Conference on Information and Knowledge Management, CIKM'08

Y2 - 26 October 2008 through 30 October 2008

ER -

Measuring user preference changes in digital libraries

Abstract

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All Science Journal Classification (ASJC) codes

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