A Comparing between the impacts of text based indexing and folksonomy on ranking of images search via Google search engine

Authors
shahnaz khademizadeh
farideh osareh
Khadijeh Mobini
Shahid Chamran University of Ahvaz
Abstract
Background and Aim: The purpose of this study was to compare the impact of text based indexing and folksonomy in image retrieval via Google search engine.

Methods: This study used experimental method. The sample is 30 images extracted from the book “Gray anatomy”. The research was carried out in 4 stages; in the first stage, images were uploaded to an “Instagram” account so the images are tagged with 600 contacts. In the second stage, the images were uploaded onto 2 blogs using text-based and folksonomy indexing, respectively. In the third stage, 118 medical experts were asked to find one of the images in Google’s image search engine. Finally, in the fourth stage, the rank of the retrieved images from the 2 blogs was reviewed.

Results: Based on the findings; in descriptive analysis, the scores of retrieved images was calculated and in the inferential analysis, independent Chi2 test was used to compare the search results of two blogs. The reported difference was significant.

Conclusion: The results showed that the folksonomy improves images’ retrieval by Google search engine compared to the text-based indexing.


Keywords
Image indexing
Folksonomy
image storing and retrieval
social platform
text-based Image Indexing
Google search engine
images ranking
social tagging
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Human and Information Interaction
Volume 5, Issue 3
Autumn 2018
Pages 15-27