UNT at ImageCLEF 2010: CLIR for Wikipedia Images Page: 1
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UNT at ImageCLEF 2010: CLIR for Wikipedia Images
Miguel E. Ruiz, Jiangping Chen, Karthikeyan Pasupathy, Pok Chin and Ryan
University of North Texas, College on Information, Department of Library and
Information Sciences, 1155 Union Circle 311068
Denton, Texas 76203-1068, USA
Abstract. This paper presents the results of the team of the University of North
Texas in the Wikipedia image retrieval track of Image-CLEF-2010. Our
approach is based on performing translation of the French and German image
captions to English and using of Language Models for generating our runs. We
also explore the use of complex queries by asking two users to manually build
queries based on the original topics distributed. Our results indicate that the
approach of translating the image captions is feasible and yields results that are
quite competitive with other teams that participated in the same track.
This paper presents the results of the UNT team participation in the Wikipedia
retrieval task. Traditionally, the most common approach to solve the cross language
retrieval problem is to perform automatic translation of the user queries into the
language of the document to be retrieved. However, in the presence of short queries
the automatic translation might not have enough context to generate an appropriate
translation. Our main goal was to explore the efficacy of using the captions associated
with the Wikipedia images and providing automatic translations of them in English.
We also address the effectiveness of using this approach using automatic queries as
well as manual queries constructed by real users.
Section 2 of this paper presents a short background of the CLIR retrieval problem
in image retrieval. Section 3 presents the methods used to conduct our experiments.
Section 4 presents our results and preliminary analysis of results. The last section of
this paper presents our conclusion and plans for future work.
Retrieval of images in multilingual collections is a task that has been studied in CLEF
since 2003 (Peters, 2009). Previous research in CLEF addressing this problem have
explored the use of different resources for translation and for most part concentrated
on combining visual and textual features automatically extracted from images
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Ruiz, Miguel E.; Chen, Jiangping; Pasupathy, Karthikeyan; Chin, Pok & Knudson, Ryan. UNT at ImageCLEF 2010: CLIR for Wikipedia Images, paper, September 2010; (https://digital.library.unt.edu/ark:/67531/metadc96836/m1/1/: accessed April 26, 2019), University of North Texas Libraries, Digital Library, https://digital.library.unt.edu; crediting UNT College of Information.