Community based feedback techniques to improve video search

David Vallet, Frank Hopfgartner, Martin Halvey, Joemon M. Jose

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

In this paper, we present a novel approach to aid users in the difficult task of video search. We use a graph based model based on implicit feedback mined from the interactions of previous users of our video search system to provide recommendations to aid users in their search tasks. This approach means that users are not burdened with providing explicit feedback, while still getting the benefits of recommendations. The goal of this approach is to improve the quality of the results that users find, and in doing so also help users to explore a large and difficult information space. In particular we wish to make the challenging task of video search much easier for users. The results of our evaluation indicate that we achieved our goals, the performance of the users in retrieving relevant videos improved, and users were able to explore the collection to a greater extent.
LanguageEnglish
Pages289-306
Number of pages8
JournalSignal, Image and Video Processing
Volume2
Issue number4
Early online date21 Oct 2008
DOIs
Publication statusPublished - 2008

Fingerprint

Feedback

Keywords

  • video
  • search
  • collaborative
  • implicit
  • feedback
  • user study

Cite this

Vallet, David ; Hopfgartner, Frank ; Halvey, Martin ; Jose, Joemon M. / Community based feedback techniques to improve video search. In: Signal, Image and Video Processing. 2008 ; Vol. 2, No. 4. pp. 289-306.
@article{c6d6eca4a3d44567baad99b0ad56d6fa,
title = "Community based feedback techniques to improve video search",
abstract = "In this paper, we present a novel approach to aid users in the difficult task of video search. We use a graph based model based on implicit feedback mined from the interactions of previous users of our video search system to provide recommendations to aid users in their search tasks. This approach means that users are not burdened with providing explicit feedback, while still getting the benefits of recommendations. The goal of this approach is to improve the quality of the results that users find, and in doing so also help users to explore a large and difficult information space. In particular we wish to make the challenging task of video search much easier for users. The results of our evaluation indicate that we achieved our goals, the performance of the users in retrieving relevant videos improved, and users were able to explore the collection to a greater extent.",
keywords = "video, search, collaborative, implicit, feedback, user study",
author = "David Vallet and Frank Hopfgartner and Martin Halvey and Jose, {Joemon M.}",
year = "2008",
doi = "10.1007/s11760-008-0087-y",
language = "English",
volume = "2",
pages = "289--306",
journal = "Signal, Image and Video Processing",
issn = "1863-1703",
number = "4",

}

Community based feedback techniques to improve video search. / Vallet, David ; Hopfgartner, Frank; Halvey, Martin; Jose, Joemon M.

In: Signal, Image and Video Processing, Vol. 2, No. 4, 2008, p. 289-306.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Community based feedback techniques to improve video search

AU - Vallet, David

AU - Hopfgartner, Frank

AU - Halvey, Martin

AU - Jose, Joemon M.

PY - 2008

Y1 - 2008

N2 - In this paper, we present a novel approach to aid users in the difficult task of video search. We use a graph based model based on implicit feedback mined from the interactions of previous users of our video search system to provide recommendations to aid users in their search tasks. This approach means that users are not burdened with providing explicit feedback, while still getting the benefits of recommendations. The goal of this approach is to improve the quality of the results that users find, and in doing so also help users to explore a large and difficult information space. In particular we wish to make the challenging task of video search much easier for users. The results of our evaluation indicate that we achieved our goals, the performance of the users in retrieving relevant videos improved, and users were able to explore the collection to a greater extent.

AB - In this paper, we present a novel approach to aid users in the difficult task of video search. We use a graph based model based on implicit feedback mined from the interactions of previous users of our video search system to provide recommendations to aid users in their search tasks. This approach means that users are not burdened with providing explicit feedback, while still getting the benefits of recommendations. The goal of this approach is to improve the quality of the results that users find, and in doing so also help users to explore a large and difficult information space. In particular we wish to make the challenging task of video search much easier for users. The results of our evaluation indicate that we achieved our goals, the performance of the users in retrieving relevant videos improved, and users were able to explore the collection to a greater extent.

KW - video

KW - search

KW - collaborative

KW - implicit

KW - feedback

KW - user study

UR - http://link.springer.com/journal/11760

U2 - 10.1007/s11760-008-0087-y

DO - 10.1007/s11760-008-0087-y

M3 - Article

VL - 2

SP - 289

EP - 306

JO - Signal, Image and Video Processing

T2 - Signal, Image and Video Processing

JF - Signal, Image and Video Processing

SN - 1863-1703

IS - 4

ER -