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Categorization of Known-Item Search Terms in a TV Archive

Published:07 March 2017Publication History

ABSTRACT

This paper reports on a preliminary explorative study that categorizes search terms provided by 50 users after having watched short clips from TV programs from The Norwegian Broadcasting Corporation archive. The aim of this study is to improve indexing by gaining knowledge about users preferred search terms. One clip is from a news program, and two clips come from a literature program. The search terms are categorized according to The Panofsky-Shatford mode/facet matrix. The study shows that specific search terms like named entities are used the most for both genres, and that generic and abstract terms are more important in the literature clips than the news clip. The search terms provided by users were matched with text from the subtitles from the clip, and the results showed that 17%, 32% and 40% of the terms were found for literature clip 1, literature clip 2 and news clip respectively. The percentage was higher when the terms were matched with subtitles from the whole program, and would have been even higher if additional on-screen text was included.

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  1. Categorization of Known-Item Search Terms in a TV Archive

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        • Published in

          cover image ACM Conferences
          CHIIR '17: Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval
          March 2017
          454 pages
          ISBN:9781450346771
          DOI:10.1145/3020165
          • Conference Chairs:
          • Ragnar Nordlie,
          • Nils Pharo,
          • Program Chairs:
          • Luanne Freund,
          • Birger Larsen,
          • Dan Russel

          Copyright © 2017 ACM

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          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 7 March 2017

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          Acceptance Rates

          CHIIR '17 Paper Acceptance Rate10of48submissions,21%Overall Acceptance Rate55of163submissions,34%

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