Beyond Shot Retrieval: Searching for Broadcast News Items Using Language Models of Concepts

Robin Aly, Aiden Doherty, Djoerd Hiemstra, Alan Smeaton

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

9 Citations (Scopus)
137 Downloads (Pure)


Current video search systems commonly return video shots as results. We believe that users may better relate to longer, semantic video units and propose a retrieval framework for news story items, which consist of multiple shots. The framework is divided into two parts: (1) A concept based language model which ranks news items with known occurrences of semantic concepts by the probability that an important concept is produced from the concept distribution of the news item and (2) a probabilistic model of the uncertain presence, or risk, of these concepts. In this paper we use a method to evaluate the performance of story retrieval, based on the TRECVID shot-based retrieval groundtruth. Our experiments on the TRECVID 2005 collection show a significant performance improvement against four standard methods.
Original languageUndefined
Title of host publicationProceedings of the 32nd European Conference on IR Research (ECIR 2010)
EditorsCathal Gurrin, Yulan He, Gabriella Kazai, Udo Kruschwitz, Suzanne Little, Thomas Roelleke, Stefan Rüger, Keith van Rijsbergen
Place of PublicationLondon
Number of pages12
ISBN (Print)978-3-642-12274-3
Publication statusPublished - 2010
Event32nd European Conference on Information Retrieval, ECIR 2010: (IR Resarch) - Milton Keynes, United Kingdom
Duration: 28 Mar 201031 Mar 2010
Conference number: 32

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Verlag
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference32nd European Conference on Information Retrieval, ECIR 2010
Abbreviated titleECIR
Country/TerritoryUnited Kingdom
CityMilton Keynes


  • IR-71235
  • EWI-17850
  • METIS-270807

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