The Magnitude and Precision of Image Retrieval in Search Engines Bing, Google and Aol

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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).

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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 .html



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