Todays, websites have great importance in the field of information and do a lot of services. In this regard, webometrics studies has been the attention of many researchers at various aspects. The aim of this study is to evaluate and cluster the Iranian banks and financial institutions based on website traffic indicators. In research process, 31 banks and financial institutions were evaluated in the form of 6 of the most important website traffic indicators include the average number of pages visited, average time to browse the site, the percentage of visitors within the country, the percentage of visitors from abroad, the number of links, and the speed of loading, based on the Alexa website and search engine. Then, the similar banks and institutions were classified in the form of homogeneous groups using by the Hierarchical Clustering Analysis (HCA). The quality and validity of each of the clusters created was confirmed by using Discriminant Analysis (DA) and finally, were discussed the characteristics of each of these clusters. The findings suggest that there is not a significant difference in terms of speed of loading between the clusters, but in other indexes, the difference between clusters is significant.

The main purpose of the research was to compare search engines performances in retrieving results for navigating querries. five search engines including Google, Yahoo, Bing, Ask, AOL were selected based on the Alexa rating scores. 011 questions in Persian along with the exact statement of question, a short description of information need, and the intended URLs were collected from the students. All 011 querries were searched in the selected search engines and the position of the correct results were recorded. For calculating the retrieving performance for the navigating querries several scales such as N success scale and reverse mean scores were used. Findings/ three search engines consisting Google, AOL, and Ask had somehow good results for navigating querries in Persian with the success rate of 364, 304, and 214, respectively. Nonetheless, Yahoo and Bing with 354 and 414 unsuccessful results had poor performances. Most results by Google, AOL, and Ask were retrieved in the first page.The search engines in 314 of cases were capable of retrieving requested items on the first page.

In this paper Special Intelligent Search Engine (SISE) design has been introduced. Also System architecture and methods of this component of its intelligent search engine and features have been described. For this intelligent robot, a "Directory" designed that aims to build professional knowledge base for quick and easy access to information for user. First of all specialized keywords were defined in the list based on the sites were indexed. 86% of the population tested, believed that the time spent searching for information SISE was lower than other general search engines and 80% believed that quality and accuracy of search results is SISE were more than other search engines.

Image indexing based on search engines in retrieving text-based and content-based indexed images using the Delphi technique.
This research is applied in terms of classifying research according to the method of data collection (research design), using the Delphi technique, and in terms of classifying research according to the purpose. The statistical population of the qualitative stage of this research included all the specialists who worked in the offices of national newspapers in Tehran and had sufficient aristocracy and mastery in all five search engines studied. Most of them, depending on the type of activity and field of work, work with a maximum of one or two search engines and are aware. Therefore, only 16 specialists were selected as the available sample for Delphi panel members. In the present study, the experts reached a general consensus with twenty questions in four stages, which were indexed based on a range of five Likert options (from very weak to very good). Given the low Kendall coefficient in the fourth round, the low agreement of the panel members, and the significance of the third round, it is concluded that there was no increase in agreement in this round, and the polling process should be stopped. In this study, after reviewing the existing texts and sources by documentary method (library study), 150 specialized questions in the field were collected. After discussion and exchange of views with experts and professors in this field, 31 questions were approved for implementation, which with 3 main components separately [image search engine evaluation criteria (nineteen questions), image retrieval based on text-based indexing (six questions), And image retrieval was performed based on content-based indexing (six questions). In the meantime, Hamshahri newspaper, with its various publications as well as provincial special issues, magazines (My Land, 24, Children, Health, Youth, Stories, Knowledge, Clues, Story Books, Advertising Brochures, Exhibition Brochures, etc.) [In addition to the 5 selected image search engines, there were other very good image search engines in this field that even ranked very well on Alexa (the international website for ranking sites and blogs); However, due to the lack of use of this language and inefficiency in Iran and the lack of a specific audience, we have ignored their choice in this study]. The results of 9 experts showed that the questionnaire's relative validity coefficient of 32 items out of 40 items was higher than the critical coefficient value of 0.78. However, the relative validity of the eight-item content was less than the critical coefficient and was omitted. Therefore, in the relative coefficient index, the content validity of 32 questionnaire items was confirmed. Also, the content validity index of the other 31 questionnaire items was higher than the standard value of 0.79. As a result, 31 questionnaire items were approved in terms of two relative content validity coefficients. In addition, Cronbach's alpha coefficient for the reliability of the questionnaire with 31 items on 16 experts showed that it is equal to 0.916, which is a high coefficient.
Google's search engine showed a higher 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, the 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. The results of the present study indicate that: 1. In the search engines, from the point of view of experts in the field of image retrieval based on text-based indexing, there are more or fewer differences, so the highest average, in this case, belonged to the Google search engine, and the lowest average belonged to the Pinterest search engine. 2. Experts in image retrieval based on content-based indexing see some differences between the search engines, so the Yandex search engine showed the highest average in this case, and the Yahoo search engine had the lowest average among the surveyed search engines. 3. Regarding image retrieval based on evaluation criteria, there are some differences between the average search engines from the perspective of experts. Hence, the average Google search engine is higher than the average of other search engines, while the Yandex search engine, in this case, is the lowest. Has had an average. 4. From the experts' point of view, there are differences between the studied search engines regarding the most efficient search engine in retrieving images based on the researched areas. The results show that Google's search engine has a much higher average than other studied search engines and the lowest average. Has been to the Pinterest search engine.
Google's general search engines perform better than other search engines (Yahoo, Bing, Pinterest, and Yandex) in retrieving images; web image searchers can also choose 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 retrieve images better. In conclusion, it is suggested that to pay more attention to the indexing and retrieval of images in search engines; designers should consider such features based on the main components identified separately: A. Criteria for image search engines (add a special code for image copyright, apply all components of this research as a menu and submenu in image search engines, notify the owners of the email (images) when uploading images for support) B. Consider image retrieval based on content-based indexing (possibility to combine multiple colors simultaneously, searchable image edges to be able to draw shapes, simultaneous searchability of image content information).

The main pupose of this study was to identify capabilities and differences among search engines in retrieving images from a text-based and content-based indexing approach. The present study was an applied research using an evaluative method.Five accessible search engines, e.g., Google, Yahoo, Picsearch, Lycos,and Exalead were selected as the research population. To gather the required information, observation and a checklist were developed based on three major components (criteria search engines for images, image retrieval based on content and context and content), with their eleven subparts. Findings showed that "Google" had the most desirable condition in retrieving images in comparison with other search engines and it was identified as the most efficient search engine. In next positions, "Yahoo", "Lycos",: Exalead", "Picsearch" were respectively ranked based on frequency distribution. Also regarding the research hypothesis, findings showed that there was a significant difference among independent groups in terms of image retrieval. The results indicated that general search engines had good performance in comparison to specialized ones. So the users of images on the Web can select the appropriate search engine based on their needs.

Using correspondence analysis, this study aims to evaluate the Iranian Medical Universities websites based on six criteria obtained from Alexa Internet. 41 medical universities websites affiliated to The Ministry of Health and Medical Education were identified on the Web. The research findings provide an evaluation of medical universities websites status in terms of their functions and performance on the Web. Results show that most of universities websites did not act successfully on the Web regarding the six criteria. The investigated websites had a weak function in traffic rank and most of them were ranked top of 100'000. As a whole, Tehran and Shiraz universities acted more successful in comparison to others whilst Qom university was weak regarding most of the criteria. Correspodence analysis classified 41 websites into 3 groupings which were related based on some attributes.

This paper aims to design proposed model for search engine designers to promote loyalty levels of search engine users. This is a descriptive survey study. The statistical population of the research is composed of Ferdowsi University students. The sample size estimated to be 347. Data gathering instrument was a self administered questionnaire and structural equation modeling (SEM) is used for the data analysis. Findings indicate that user communication affects user satisfaction significantly and negatively. Also in research final model search engine image، search engine perceived quality and search engine perceived value affects user satisfaction. Moreover، search engine perceived value affects user loyalty and verbal advertising directly. Also user satisfaction affects user loyalty directly. Finally user loyalty leads into high expected switching costs، search engine revisit and verbal advertising for search engines.

using search engines is a way to retrieve information. The aim of this study was to evaluate and compare the recall and accuracy of general search engines, based on the system relevance and search logic.
This comparative study was done using three key words” scientometry”, “scientific production” and “citation analysis” which based on searched keywords in IranDoc are the most frequent during 1389-1393 in the field of information sciences. These keywords were searched in Google- Yahoo- Bing- Ask- AOI using Boolean search logic operation (AND), fuzzy logic (the short way) and vector model in English. According to search logic first 10 results per search engine were saved then the recall and accuracy were calculated.
Findings and In all three logic search Google had the highest level of accuracy and recall (accuracy: 0.833 ± 0. 20 and recall: 0.125 ±0.03) and Bing had the lowest levels (Accuracy: 0.277± 0.12 and recall: 0.41 ± 0.02), ASK was at the second level in all three methods and AOL and Bing had the weakest function in vector model and truncation respectively. Google with Boolean logic had the most and with truncation had the least relevant documents. ASK in the three search logic had a same level of relevancy, Yahoo with Boolean logic search had the lowest and with vector model had the highest number of relevant documents. Bing had the lowest relevant documents with truncation and eventually AOL was at the lowest operating level with vector model.