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User controllability in a hybrid rec...

Parra Santander, Denis Alejandro.

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User controllability in a hybrid recommender system.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	User controllability in a hybrid recommender system./
Author:	Parra Santander, Denis Alejandro.
Description:	195 p.
Notes:	Source: Dissertation Abstracts International, Volume: 75-03(E), Section: B.
Contained By:	Dissertation Abstracts International75-03B(E).
Subject:	Information Technology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3577036
ISBN:	9781303590726

User controllability in a hybrid recommender system.
Parra Santander, Denis Alejandro.

User controllability in a hybrid recommender system. - 195 p.

Source: Dissertation Abstracts International, Volume: 75-03(E), Section: B.

Thesis (Ph.D.)--University of Pittsburgh, 2013.

Since the introduction of Tapestry in 1990, research on recommender systems has traditionally focused on the development of algorithms whose goal is to increase the accuracy of predicting users' taste based on historical data. In the last decade, this research has diversified, with human factors being one area that has received increased attention. Users' characteristics, such as trusting propensity and interest in a domain, or systems' characteristics, such as explainability and transparency, have been shown to have an effect on improving the user experience with a recommender. This dissertation investigates on the role of controllability and user characteristics upon the engagement and experience of users of a hybrid recommender system. A hybrid recommender is a system that integrates the results of different algorithms to produce a single set of recommendations. This research examines whether allowing the user to control the process of fusing or integrating different algorithms (i.e., different sources of relevance) results in increased engagement and a better user experience. The essential contribution of this dissertation is an extensive study of controllability in a hybrid fusion scenario. In particular, the introduction of an interactive Venn diagram visualization, combined with sliders explored in a previous work, can provide an efficient visual paradigm for information filtering with a hybrid recommender that fuses different prospects of relevance with overlapping recommended items. This dissertation also provides a three-fold evaluation of the user experience: objective metrics, subjective user perception, and behavioral measures.

ISBN: 9781303590726Subjects--Topical Terms:

1030799
Information Technology.

User controllability in a hybrid recommender system.
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020 $a 9781303590726
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100 1 $a Parra Santander, Denis Alejandro. $3 2099756
245 1 0 $a User controllability in a hybrid recommender system.
300 $a 195 p.
500 $a Source: Dissertation Abstracts International, Volume: 75-03(E), Section: B.
500 $a Adviser: Peter Brusilovsky.
502 $a Thesis (Ph.D.)--University of Pittsburgh, 2013.
520 $a Since the introduction of Tapestry in 1990, research on recommender systems has traditionally focused on the development of algorithms whose goal is to increase the accuracy of predicting users' taste based on historical data. In the last decade, this research has diversified, with human factors being one area that has received increased attention. Users' characteristics, such as trusting propensity and interest in a domain, or systems' characteristics, such as explainability and transparency, have been shown to have an effect on improving the user experience with a recommender. This dissertation investigates on the role of controllability and user characteristics upon the engagement and experience of users of a hybrid recommender system. A hybrid recommender is a system that integrates the results of different algorithms to produce a single set of recommendations. This research examines whether allowing the user to control the process of fusing or integrating different algorithms (i.e., different sources of relevance) results in increased engagement and a better user experience. The essential contribution of this dissertation is an extensive study of controllability in a hybrid fusion scenario. In particular, the introduction of an interactive Venn diagram visualization, combined with sliders explored in a previous work, can provide an efficient visual paradigm for information filtering with a hybrid recommender that fuses different prospects of relevance with overlapping recommended items. This dissertation also provides a three-fold evaluation of the user experience: objective metrics, subjective user perception, and behavioral measures.
590 $a School code: 0178.
650 4 $a Information Technology. $3 1030799
650 4 $a Computer Science. $3 626642
650 4 $a Technical Communication. $3 1669287
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710 2 $a University of Pittsburgh. $b Information Science. $3 2099757
773 0 $t Dissertation Abstracts International $g 75-03B(E).
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791 $a Ph.D.
792 $a 2013
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3577036