Knowledge Management
soudabeh derakhshandeh; Fereshteh Sepehr; zahra abazari; neshaneh neshaneh
Abstract
Background and objective: Image indexing based on search engines in retrieving text-based and content-based indexed images using the Delphi technique.
Methodology: In terms of purpose, application and type of research using Delphi technique. The statistical population includes all specialists working ...
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Background and objective: Image indexing based on search engines in retrieving text-based and content-based indexed images using the Delphi technique.
Methodology: In terms of purpose, application and type of research using Delphi technique. The statistical population includes all specialists working in the offices of national newspapers in the city of Tehran who have sufficient aristocracy and mastery in all five search engines studied. The number of these 16 specialists was available as a sample in the study area. To collect data by documentary method, research items were extracted and Delphi questionnaire was compiled. Experts reached a general consensus in four stages with twenty questions based on a range of five Likert options. The results of the Kendall agreement coefficient test were reported to determine the degree of coordination and consensus among the experts' response in each round for comparison and comparison. By confirming the questionnaire in the qualitative section of content validity, the quality validity coefficient of the content of the questionnaire was higher than 0.78 and the content validity index was higher than 0.79 The reliability of the questionnaire was measured based on Cronbach's alpha coefficient equal to 0.916.
Findings: Google search engine showed more image retrieval rate based on their evaluation criteria. There was no significant difference between the studied search engines from the perspective of experts in the field of image retrieval based on text-based indexing at the level of P <0.05 Yandex search engine has a higher content indexing based on indexing based on more content at the level of P <0.05 . Also, Google search engine is significantly more efficient at the level of P u003c0.05 in terms of retrieving images based on the areas under study.
Discussion: Google general search engines were found to perform better than other search engines (yahoo, bing, pinterest and yandex) in retrieving images; Web image searchers can also decide on the search engine that suits their needs and interior designers for better design. In addition, these results can be generalized to similar areas, and search engine designers will find out which indexing method to use to better retrieve images.
Saleh Rahimi; Hamid Keshavarz; Mahdi Khademian
Abstract
Purpose: the current research aimed to compare the effectiveness of various tags and codes for retrieving images from the Google. Design/methodology: selected images with different characteristics in a registered domain were carefully studied. The exception was that special conceptual features have been ...
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Purpose: the current research aimed to compare the effectiveness of various tags and codes for retrieving images from the Google. Design/methodology: selected images with different characteristics in a registered domain were carefully studied. The exception was that special conceptual features have been apportioned for each group of images separately. In this regard, each group image surrounding texts was dissimilar. Images were allocated with captions including language in Farsi and English, alt text, image title, file name, free and controlled languages and appropriation text to images properties. Findings: allocating texts to images on website causes Google retrieve more images. Chi-square test for difference of retrieved images in 5 Codes is significant and revealed that in different codes, significantly various numbers of images were retrieved. Caption allocation in English had the best effect in retrieving images in the study sample and file name had less effect in image retrieval ranking. image retrieval
