Objectives: The purpose of this study was to determine the comprehensiveness and precision of the two engines exploring Bing and Google in image retrieval. The purpose of this is to find the search engine that has the most comprehensive and precise, in the recovery of images.
Methodology: The present study is of a type, applied, and has used quasi-experimental research in terms of purpose and data collection. The community of this research, the images stored in the image bases of two search engines, Bing and Google. Research data was compiled from image – to-image searches in search engines by style, content-centered images, and direct viewing of retrieved sources.
Then, using the relevance formula, the comprehensiveness and precision of the search results were calculated in each search engine. Then, the average percentages were calculated for the comprehensive and precise scores of each search engine. Then, based on the collected data, the research hypotheses were tested using U-Mann-Whitney statistical test.
Findings: Findings show that Google’s search engine with 88.73% comprehensiveness had a higher ranking in recovery, and Bing’s crawling engine with an average of 86.8% was comprehensive, had a low recovery rate.
Also, Bing’s search engine with 96.66% higher ranking was in precision, and Google’s search engine with 94.8% of the post-Bing percentage remained. The hypothesis test showed that there is a significant difference between the comprehensiveness of the search engines with 95% confidence. But there was no significant difference between the level of their balance.
Introduction and expression of the problem
In the present era, we are witnessing the ever-increasing growth of science and technology, and based on this, the variety of information in various formats is increasing and becoming more massive every day.
In this process, users are confronted with the confusion and difficulty of retrieving information. By expanding the World Wide Web and increase
ing the volume of a variety of multimedia objects (text, video, audio, video, animation, and so on), indexing specialists have developed their activities based on this global network to organize this massive information (Rawski, 2007).
Undoubtedly, this huge amount of information needs to be organized, so that when searching, access to speed and ease is done. The main mission of any library or information environment is to provide the information available to them based on the users’ needs. In order to accomplish this task, information stored in library or information environments should be indexed based on a set of principles, methods, and tools, help improve information retrieval from the tank.
Throughout history, the development and expansion of libraries and information centers has been used to provide information, two important activities for organizing information, and these two activities have been indexed and indexed. Therefore, indexing is one of the main activities in the field of information processing and has a significant effect on data retrieval (Hidderley, & Rafferty, 2005).
Now many websites are designing a program to search within their website. These programs, like full – text files, can have irrelevant evidence in their search results, with so – called false crashes. If on such web – sites, like the ones at the end of the books, there is a kind of web-site, the user can quickly and easily use the profile list to enter the desired entry and, at a high speed and with little time to complete his required documents, and even to the documents Related to it also. Some web search tools try to review web sites by experts, and after analyzing content, select relevant keywords and place them in the subject area based on their specific topic list.
These tools provide an in – depth guide for users. In principle, doing so essentially means that search engines typically index all pages to guide the site to the website, but on the other hand, it’s a very similar subject – matter guide to its internal link, ( Tyner, 2001).
As noted, in the global web environment, a variety of multimedia information stored, and each indexed in a manner that is accessible. One of the types of information on the web is images.
Pictures are now the most accepted, available data on the web. The web is an important source for finding pictures. An area of indexing is the search and retrieval of images, which has always faced major challenges (Kokbabi, 2013).
The system of retrieval used for databases has its own specific complexity and research on the structure, operation, and methods of storing and retrieving database and search engine can provide more livelier horizons to the designers of these types of recovery systems(Nkere u wem, Edet , 1992).
This study not only reduces the ambiguity and challenges of retrieving images, but also ensures ease of retrieval and access for users to require images and improves the quality and relevance of images obtained from the search engine.
Therefore, as a subset of the storage and retrieval system, the integrity and precision in retrieving a large number of images from an image database is a major issue. From a different perspective, images, while rich, can be useful to researchers in the future. For example, a series of photos of a century – old prospect may be useful to historians. But these images also often contain infected data.
Pictures as one type of information on the World Wide Web, as with other types of information, such as text, audio, video, and so on. Every day, millions of images are placed on search engines and internet sites, and due to their bulkiness, they do not have access to the problem.
However, it is necessary for them to be organized in such a way as to allow access to everyone as easily and as quickly as possible. Indexing as one of the most desirable ways of organizing information, today, in addition to its traditional form, the end pages of the book, has also shown its effectiveness on the Internet. The multimedia information in the search engines database is massive and is increasing day by day and endangers users with the problem.
Indexing in databases, search engine images, to provide a query for the images. Each image has a unique attribute; therefore, indexing images can be done by comparing their profiles, which are extracted from the images itself.
Except for image exploration engines, there are certain existing databases on the World Wide Web, Bing, Google, and EOL, public search engines for the images contained therein(Shera,2013).
During the research, the researcher found that his exploration engine did not have the ability to search images in content. Not only does not have the ability to search the image with the image, but also in the search restriction area, it is not possible to specify the content properties of the image, which includes color, texture, and shape; therefore, the exploration engine was removed from the evaluation, and thus compared The two Google and Bing search engines that benefited from this were dealt with.
Now, with regard to the issues mentioned, the researcher intends, in an adaptive manner, to examine the comprehensiveness and precision of the two search engine engines.
Conclusion and ending speech:
With the introduction and influence of information technology, and in particular the World Wide Web, in different areas of life, and increasing the importance of image, in various areas, the need to address their images and their role is felt more and more.
Although it seems that the domain of images is something that may have been important in the past, more than any kind of information, and each image has played the role of thousands of words. But at the same time, we realize that the issue of storage and retrieval of images has been neglected, and in recent years has attracted the attention of experts in this field more than ever. Now, it turns out that the image plays an important role in culture, education, social issues, medicine, and so on.
Now, addressing the issue of data retrieval is critical at any moment. Until now, the subject of image retrieval remains much the same as the theory and the premise, and the research that is applied to this issue is rarely addressed , There have been. In the present study, we tried to take a small step, in this area, to be removed.
Obviously, in each research, a small part of a field is considered and examined, and the findings of a research can only answer the questions of the same research and generalize in the scope and scope of the same research.
In the present study, the findings concerning the content retrieval of images were reported in two Bing and Google search engines; only the same content is true, while the conceptual recovery of images may not be the same.
According to the findings of the research on two variables of completeness and imprinting, it can be concluded that the comprehensiveness of two Bing and Google search engines, which is 20.86 and 88.73, respectively, and the test of the first hypothesis of comprehensiveness, has a significant difference between the two engines Explore shows and this difference is in favor of Google’s Explore Engine.
Therefore, it can be said that according to the findings, Google’s search engine for users who are looking for greater integrity is a good option and has a better performance than competing search engine, in other words, the Bing search engine is for users who are looking for greater integrity.
Is not a good option. Testing the second hypothesis of the imprint, shows that the level of the balance between two Bing and Google search engines, which are 96.66 and 94/80, respectively, and there is no significant difference between the two search engines, it can be said that both for users Looking for more precision in image retrieval is a good option, but given the high percentage of Bing’s search engine visibility over Google, this Bing search engine is preferred to users who are looking for more resilience in retrieval.
In retrieving information, it is desirable that the level of completeness and imprinting are equal, but usually the search for the search engines as well as the search engines will increase the level of completeness, the lower the margin, and the more the margin becomes more comprehensive becomes less .
The results of this study are as follows: the comprehensiveness of Google’s search engine is reater, resulting in less visibility than the Bing search engine, and the Bing search engine is less comprehensive, but has a relatively higher level of orientation than Google’s search engine.
It is hoped that the present study will provide a tiny step for understanding the status quo in this subject area, as well as providing a small contribution to the large scientific and research community, and pave the way for future research
Hidderley, R., & Rafferty, P. (2005). Indexing multimedia and creative works: The problems of meaning and interpretation. New York: Ashgate publishing company.
Kokbabi, Morteza, Rahimi, Saleh, Extract, Farideh, and Norouzi, Alireza (2013). Reflections on indexing images: An illustration worth a thousand words. Information Research and Public Libraries, 19 (2), 257-276.
Nkere u wem, Edet E. (1992). “The Correlation between Job Attitudes and Work Behavior among the Staff in Academic Libraries in Nigeria”. Information services and use, 12 (31,253-261).
Rawski. Conrad H (2007). “Toward a Theory of Librarianship: Papers in Honor of Jesse Haok Shera”. Metuchen, N.J.: the scare crow press. 14-55, 116-147.
Shera, Jesse H. (2013). “The Foundations of Education for Librarianship”. New York Becker and Hayes Inc.
Tyner, Ross (2001). Sink or swim: internet search tools & techniques. Retrieved October 8, 2014, from http://www.ouc.bc.ca/libr/connect96/search .html
DOWNLOAD THE COMPLETE RESEARCH PAPER PDF
109 total views, 1 views today