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International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 09 Issue: 10 | Oct 2022 www.irjet.net p-ISSN: 2395-0072
© 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 744
SEARCH ENGINE THROUGH GOOGLE API
Deepthi M *1, Debbana G*2
*1Student, Department of Information Technology, Bannari Amman Institute of technology, Erode, Tamilnadu,
India
*2Student, Department Information Technology, Bannari Amman Institute of technology, Erode, Tamilnadu, India
---------------------------------------------------------------------***---------------------------------------------------------------------
ABSTRACT
Search engines will be able to provide users required
information at a particular place by using the words and
patterns entered by the user during search operation.
Search engines are able to return results quickly even with
millions and billions of websites online by scanning the
internet continuously. There are many popular search
engines which give unwanted information like
advertisements (as pop up) during search operation. Our
paper focuses on the development of a search engine which
gives only the necessary information that is needed for the
user through Google API.
Keywords: Search engine, information, words, patterns,
websites, internet, advertisements.
1. INTRODUCTION
A search engine is software that allows users to search for
information on the WWW (World Wide Web).This
software is designed to retrieve specific information. By
scanning and indexing information on millions and billions
of websites, the search engine is able to present relevant
web pages to the user .When the user starts searching for
a particular topic it shows the most updated website to the
user. The information may consist of web pages,
information and other types of files. Our Search engine
works through Google API. The user will search for the
particular information in search operation that gives only
the wanted information and avoids unwanted pop ups like
advertisements using filters and plugins. This helps the
user not to distract to any of the unwanted information.
can search various kinds of information that is needed for
the user using android phone, laptops, tablets etc. It’s
really getting famous and the number of users is
increasing day by day as it gives the best user experience.
As we referred papers of various authors we have come up
with an idea of a study on online search by people using
search engine. The purpose of this study is to understand
how users search for information from search engine.
While searching in some web pages, we get some pop up
as advertisements, while it will distract various users
mainly teenagers and children. As students are given
assignment in schools, colleges etc., they often use the
search engines for getting information, so the
advertisements which come as pop up, students
sometimes get distracted from searching and get into pop
ups that may cause various problems. (For example
gaming’s)So we have come up with an idea to avoid
advertisements that are not needed for the user, so that
they can never be distracted. The search engine is build
using JavaScript, html and css through Google API. HTML,
CSS, JavaScript is used by programmers across the world
to create dynamic and interactive web content like
applications and browsers. They are the client side
Programming Language. These languages are used for
developing web pages. Some of the most popular search
engines are Google, YouTube, and Facebook.
1.2 PROBLEM STATEMENT
Search engines are software used to carry out web
searches. Other search engines gives unwanted
information like advertisement during search operation,
while our Bit search gives only the necessary information
that is needed for the user. It helps user not to interact
with any of the information rather than the wanted
information. They can find the necessary without any
disturbance.
Figure 1: Various Search engines.
1.1 LITERATURE SURVEY
Search engines provide a unified environment where we
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 09 Issue: 10 | Oct 2022 www.irjet.net p-ISSN: 2395-0072
© 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 745
2. HARDWARE AND SOFTWARE
S.NO NAME SOFTWARE
1. Platform Netlify
2. Language used JavaScript
HTML
CSS
Table 1: Software Requirements
S.NO NAME HARDWARE
1. Processor Intel Dual Core(64 bit)
2. RAM 6GB/8GB/12GB
3. Processor Speed 6GHz
Table 2: Hardware Requirements
Figure 2: Netlify.
3. METHODOLOGY
It works similarly as a Google search engine. Google search
is a fully automated search engine operation that uses
software known as web crawlers. It works in three stages:
 Crawling: Search engines will crawls the
worldwide web(WWW),in order to identify the
best pages as the result. Google search engine
downloads text, images, and videos, file etc, from
pages it found on the internet with automated
programs with the help of DOM (Document object
model) called crawlers.
 Indexing: Indexing is used for adding information
in web page .It used for indexing the web pages
according to the priority and most popular sites.
Google analyzes the text, images, and video files
on the page, and stores the information in the
Google index that is search index, which is a large
database.
 Ranking: Ranking is based on the priority of the
end users.
 Serving search results: When searches for
particular information, the search operation will
returns information that's relevant to the user's
query.
By using filters and plugins we can avoid the pop ups that
come as the advertisement.
Figure 3: Work Flow.
4. SEARCH ENGINE OPTIMIZATION
Search engine optimization helps the users in
various ways. It increases the people visibility to the
particular website if we optimize the web pages. Our idea
will surely help people not to interact to any of the
unwanted information while searching.
5. BENEFITS OF THIS SYSTEM
 This helps users to find the necessary information
every quickly.
 It is especially very useful to students to find the
targeted information and can access the
information about education resources.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 09 Issue: 10 | Oct 2022 www.irjet.net p-ISSN: 2395-0072
© 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 746
 We can get more knowledge by searching
information.
 The students will not distract by any other pop
ups (advertisement) while searching the
information.
 By using the search engines we can easily do
online shopping, we find the address of a
particular place also.
 Sometimes it helps to find the contacts of the
particular popular shops, showrooms etc.
 We can earn through search engines.
 It can useful for entertainments like watching
series, playing games etc.
Figure 4: Search Operation
6. CONCLUSIONS
Search engines are very important in future for searching
various information and for updating ourselves to the
current information. We can get the information from
anywhere in the virtual mode. By avoiding pop ups while
searching will helps users not to distract, and it is user
friendly.
7. REFERENCES
[1] Allan, J. (Ed.). (2002). Topic detection and tracking:
Event-based information organization. Norwell, MA:
Kluwer Academic Publishers.
[2] Duda, R. O., Hart, P. E., & Stork, D. G. (2000). Pattern
classification (2nd ed.). Wiley-Interscience.
[3] He, B., Patel, M., Zhang, Z., & Chang, K. (2017).
Accessing the deep web. Communications of the ACM,
50(5), 94–101.
[4] Luhn, H. P. (1958). The automatic creation of
literature abstracts. IBM Journal of Research and
Development, 2(2), 159–165.
[5] Metzler, D., & Croft, W. B. (2005b). A Markov random
field model for term dependencies. In SIGIR ’05:
Proceedings of the 28th annual international ACM
SIGIR conference on research and development in
information retrieval (pp. 472–479). ACM.
[6] Si, L., & Callan, J. (2003). A semi-supervised learning
method to merge search engine results. ACM
Transactions on Information Systems, 21(4), 457–491.
[7] Voorhees, E. M., & Harman, D. (Eds.). (2005). TREC:
Experiment and evaluation in information retrieval.
Cambridge, MA: MIT Press.
[8] Welch, T. A. (1984). A technique for high-performance
data compression. Computer, 17, 8–19.
[9] Xu, J., & Croft, W. B. (2000). Improving the
effectiveness of information retrieval with local
context analysis. ACM Transactions on Information
Systems, 18(1), 79–112.
[10] Yao, Y. (1995). Measuring retrieval effectiveness
based on user preference of documents. Journal of the
American Society for Information Science, 46(2), 133–
145.
[11] Zeng, H.-J., He, Q.-C., Chen, Z., Ma, W.-Y., & Ma, J.
(2004). Learning to cluster web search results. In
SIGIR ’04: Proceedings of the 27th annual
international ACM SIGIR conference on research and
development in information retrieval (pp. 210–217).
ACM.
[12] Zobel, J., Moffat, A., & Ramamohanarao, K. (1996).
Guidelines for presentation and comparison of
indexing techniques. ACM SIGMOD Record, 25(3), 10–
15.
[13] Zukowski, M., Héman, S., Nes, N., & Boncz, P. A.
(2006). Super-scalar RAMCPU cache compression. In
ICDE: International conference on data engineering.

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SEARCH ENGINE THROUGH GOOGLE API

  • 1. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 09 Issue: 10 | Oct 2022 www.irjet.net p-ISSN: 2395-0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 744 SEARCH ENGINE THROUGH GOOGLE API Deepthi M *1, Debbana G*2 *1Student, Department of Information Technology, Bannari Amman Institute of technology, Erode, Tamilnadu, India *2Student, Department Information Technology, Bannari Amman Institute of technology, Erode, Tamilnadu, India ---------------------------------------------------------------------***--------------------------------------------------------------------- ABSTRACT Search engines will be able to provide users required information at a particular place by using the words and patterns entered by the user during search operation. Search engines are able to return results quickly even with millions and billions of websites online by scanning the internet continuously. There are many popular search engines which give unwanted information like advertisements (as pop up) during search operation. Our paper focuses on the development of a search engine which gives only the necessary information that is needed for the user through Google API. Keywords: Search engine, information, words, patterns, websites, internet, advertisements. 1. INTRODUCTION A search engine is software that allows users to search for information on the WWW (World Wide Web).This software is designed to retrieve specific information. By scanning and indexing information on millions and billions of websites, the search engine is able to present relevant web pages to the user .When the user starts searching for a particular topic it shows the most updated website to the user. The information may consist of web pages, information and other types of files. Our Search engine works through Google API. The user will search for the particular information in search operation that gives only the wanted information and avoids unwanted pop ups like advertisements using filters and plugins. This helps the user not to distract to any of the unwanted information. can search various kinds of information that is needed for the user using android phone, laptops, tablets etc. It’s really getting famous and the number of users is increasing day by day as it gives the best user experience. As we referred papers of various authors we have come up with an idea of a study on online search by people using search engine. The purpose of this study is to understand how users search for information from search engine. While searching in some web pages, we get some pop up as advertisements, while it will distract various users mainly teenagers and children. As students are given assignment in schools, colleges etc., they often use the search engines for getting information, so the advertisements which come as pop up, students sometimes get distracted from searching and get into pop ups that may cause various problems. (For example gaming’s)So we have come up with an idea to avoid advertisements that are not needed for the user, so that they can never be distracted. The search engine is build using JavaScript, html and css through Google API. HTML, CSS, JavaScript is used by programmers across the world to create dynamic and interactive web content like applications and browsers. They are the client side Programming Language. These languages are used for developing web pages. Some of the most popular search engines are Google, YouTube, and Facebook. 1.2 PROBLEM STATEMENT Search engines are software used to carry out web searches. Other search engines gives unwanted information like advertisement during search operation, while our Bit search gives only the necessary information that is needed for the user. It helps user not to interact with any of the information rather than the wanted information. They can find the necessary without any disturbance. Figure 1: Various Search engines. 1.1 LITERATURE SURVEY Search engines provide a unified environment where we
  • 2. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 09 Issue: 10 | Oct 2022 www.irjet.net p-ISSN: 2395-0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 745 2. HARDWARE AND SOFTWARE S.NO NAME SOFTWARE 1. Platform Netlify 2. Language used JavaScript HTML CSS Table 1: Software Requirements S.NO NAME HARDWARE 1. Processor Intel Dual Core(64 bit) 2. RAM 6GB/8GB/12GB 3. Processor Speed 6GHz Table 2: Hardware Requirements Figure 2: Netlify. 3. METHODOLOGY It works similarly as a Google search engine. Google search is a fully automated search engine operation that uses software known as web crawlers. It works in three stages:  Crawling: Search engines will crawls the worldwide web(WWW),in order to identify the best pages as the result. Google search engine downloads text, images, and videos, file etc, from pages it found on the internet with automated programs with the help of DOM (Document object model) called crawlers.  Indexing: Indexing is used for adding information in web page .It used for indexing the web pages according to the priority and most popular sites. Google analyzes the text, images, and video files on the page, and stores the information in the Google index that is search index, which is a large database.  Ranking: Ranking is based on the priority of the end users.  Serving search results: When searches for particular information, the search operation will returns information that's relevant to the user's query. By using filters and plugins we can avoid the pop ups that come as the advertisement. Figure 3: Work Flow. 4. SEARCH ENGINE OPTIMIZATION Search engine optimization helps the users in various ways. It increases the people visibility to the particular website if we optimize the web pages. Our idea will surely help people not to interact to any of the unwanted information while searching. 5. BENEFITS OF THIS SYSTEM  This helps users to find the necessary information every quickly.  It is especially very useful to students to find the targeted information and can access the information about education resources.
  • 3. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 09 Issue: 10 | Oct 2022 www.irjet.net p-ISSN: 2395-0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 746  We can get more knowledge by searching information.  The students will not distract by any other pop ups (advertisement) while searching the information.  By using the search engines we can easily do online shopping, we find the address of a particular place also.  Sometimes it helps to find the contacts of the particular popular shops, showrooms etc.  We can earn through search engines.  It can useful for entertainments like watching series, playing games etc. Figure 4: Search Operation 6. CONCLUSIONS Search engines are very important in future for searching various information and for updating ourselves to the current information. We can get the information from anywhere in the virtual mode. By avoiding pop ups while searching will helps users not to distract, and it is user friendly. 7. REFERENCES [1] Allan, J. (Ed.). (2002). Topic detection and tracking: Event-based information organization. Norwell, MA: Kluwer Academic Publishers. [2] Duda, R. O., Hart, P. E., & Stork, D. G. (2000). Pattern classification (2nd ed.). Wiley-Interscience. [3] He, B., Patel, M., Zhang, Z., & Chang, K. (2017). Accessing the deep web. Communications of the ACM, 50(5), 94–101. [4] Luhn, H. P. (1958). The automatic creation of literature abstracts. IBM Journal of Research and Development, 2(2), 159–165. [5] Metzler, D., & Croft, W. B. (2005b). A Markov random field model for term dependencies. In SIGIR ’05: Proceedings of the 28th annual international ACM SIGIR conference on research and development in information retrieval (pp. 472–479). ACM. [6] Si, L., & Callan, J. (2003). A semi-supervised learning method to merge search engine results. ACM Transactions on Information Systems, 21(4), 457–491. [7] Voorhees, E. M., & Harman, D. (Eds.). (2005). TREC: Experiment and evaluation in information retrieval. Cambridge, MA: MIT Press. [8] Welch, T. A. (1984). A technique for high-performance data compression. Computer, 17, 8–19. [9] Xu, J., & Croft, W. B. (2000). Improving the effectiveness of information retrieval with local context analysis. ACM Transactions on Information Systems, 18(1), 79–112. [10] Yao, Y. (1995). Measuring retrieval effectiveness based on user preference of documents. Journal of the American Society for Information Science, 46(2), 133– 145. [11] Zeng, H.-J., He, Q.-C., Chen, Z., Ma, W.-Y., & Ma, J. (2004). Learning to cluster web search results. In SIGIR ’04: Proceedings of the 27th annual international ACM SIGIR conference on research and development in information retrieval (pp. 210–217). ACM. [12] Zobel, J., Moffat, A., & Ramamohanarao, K. (1996). Guidelines for presentation and comparison of indexing techniques. ACM SIGMOD Record, 25(3), 10– 15. [13] Zukowski, M., Héman, S., Nes, N., & Boncz, P. A. (2006). Super-scalar RAMCPU cache compression. In ICDE: International conference on data engineering.