Provide image indexing model based on search engines in retrieving text-based and content-based indexed images

Provide an image indexing template based on search engines to retrieve text-based and content-based indexed images

In terms of purpose,application and type of descriptive research, there is a correlation.The statistical population included experts working in the offices of national newspapers in Tehran,who were familiar with five search engines.Data collection for component design is by a researcher-made questionnaire with 20 items by documentary method.The quality validity coefficient of the content of the questionnaire is higher than 0.78 and the content validity index is higher than 0.79.The reliability of the questionnaire was measured based on Cronbach's alpha coefficient equal to0.936.

In exploratory factor analysis, 20 items studied in four factors with textual indexing factor loads (with factor load range between0.51 to 0.76), image indexing(with factor load range between0.59 to 0.74), content indexing (Loaded with factor load range between 0.57 to 0.78)and effectiveness (with factor load range between0.53 to 0.85).

Internal factor 1(text indexing)with an average factor load of 0.79plays the most important role in constructing the external factor or the overall scale, while internal factor2(image indexing) with an average factor load of0.74 is the second most important component.In the construction, the external factor was general,followed by the internal factor3(content indexing)with an average factor load of0.72; Finally,internal factor4(effectiveness)with a factor load of 0.69 had the least role in making the overall factor.The fit indices of the model, such as relative chi-square and economical indices, showed the fit to be quite appropriate.As a result, the obtained model has a relatively good fit to the data.