SEARCH ENGINE OPTIMIZATION: A REVIEW

Firas ALMUKHTAR


Imam Jaafar Al-Sadiq University (Iraq)

Nawzad MAHMOODD


Erbil Polytechnic University, Information System Engineering (Iraq)

Shahab KAREEM

shahabwk@yahoo.com
Erbil Polytechnic University, Information System Engineering (Iraq)

Abstract

The Search Engine has a critical role in presenting the correct pages to the user because of the availability of a huge number of websites, Search Engines such as Google use the Page Ranking Algorithm to rate web pages according to the nature of their content and their existence on the world wide web. SEO can be characterized as methodology used to elevate site keeping in mind the end goal to have a high rank i.e., top outcome. In this paper the authors present the most search engine optimization like (Google, Bing, MSN, Yahoo, etc.), and compare by the performance of the search engine optimization. The authors also present the benefits, limitation, challenges, and the search engine optimization application in business.


Keywords:

search engine optimization, Google, page ranking, Information Retrieve

Abdalwahid, S. M. J., Yousif, R. Z., & Kareem, S. W. (2019). Enhancing approach using hybrid Pailler and RSA for information security in BigData. Applied Computer Science, 15(4), 63–74. https://doi.org/10.23743/acs-2019-30
  Google Scholar

Amin, S. (2017). Factors Influencing the Adoption of Location Based Identification in the Kurdistan Region of Iraq. University of Huddersfield.
DOI: https://doi.org/10.24086/cuesj.si.2017.n1a9   Google Scholar

Amin, S. M., Shahab, W. K., Al Azzawi, A. K., & Sivaram, M. (2018). Time Series Prediction Using SRE- NAR and SRE- ADALINE. Jour. of Adv. Research in Dynamical & Control Systems, 10(12), 1716–1726.
  Google Scholar

Berman, R., & Katona, Z. (2013). The role of search engine optimization in search marketing. Marketing Science, 32(4), 644–651.
DOI: https://doi.org/10.1287/mksc.2013.0783   Google Scholar

Edosomwan, J., & Edosomwan, T. O. (2021). Comparative analysis of some search engines. South African Journal of Science, 106(11/12), 169. http://doi.org/10.4102/sajs.v106i11/12.169
DOI: https://doi.org/10.4102/sajs.v106i11/12.169   Google Scholar

Hawezi, R. S., Azeez, M. Y., & Qadir, A. A. (2019). Spell checking algorithm for agglutinative languages “Central Kurdish as an example”. 2019 International Engineering Conference (IEC) (pp. 142–146). IEEE.
DOI: https://doi.org/10.1109/IEC47844.2019.8950517   Google Scholar

Kareem, S. W. (2009). Hybrid Public Key Encryption Algorithms For E-Commerce. Salahadin University.
  Google Scholar

Kareem, S., & Okur, M. C. (2018). Bayesian Network Structure Learning Using Hybrid Bee Optimization and Greedy Search. Çukurova University. Adana, Turkey.
  Google Scholar

Kareem, S., & Okur, M. C. (2020a). Evaluation of Bayesian Network Structure Learning Using Elephant Swarm Water Search Algorithm. In S. C. Shi (Ed.), Handbook of Research on Advancements of Swarm Intelligence Algorithms for Solving Real-World Problems (pp. 139–159). IGI Global.
DOI: https://doi.org/10.4018/978-1-7998-3222-5.ch008   Google Scholar

Kareem, S., & Okur, M. C. (2020b). Structure Learning of Bayesian Networks Using Elephant Swarm Water Search Algorithm. International Journal of Swarm Intelligence Research, 11(2), 19–30. https://doi.org/10.4018/IJSIR.2020040102
DOI: https://doi.org/10.4018/IJSIR.2020040102   Google Scholar

Kareem, W. S., Yousif, R. Z., & Abdalwahid, S. M. J. (2020). An approach for enhancing data confidentiality in Hadoop. Indonesian Journal of Electrical Engineering and Computer Science, 20(3), 1547–1555. http://doi.org/10.11591/ijeecs.v20.i3.pp1547-1555
DOI: https://doi.org/10.11591/ijeecs.v20.i3.pp1547-1555   Google Scholar

Keti, F., & Askar, S. (2015). Emulation of software defined networks using mininet in different simulation environments. 6th International Conference on Intelligent Systems, Modelling and Simulation (pp. 205–210). IEEE. http://doi.org/10.1109/ISMS.2015.46
DOI: https://doi.org/10.1109/ISMS.2015.46   Google Scholar

King, A. B. (2008). Website Optimization. O'Reilly Media, Inc.
  Google Scholar

Mohamed, J. M., & Khoshaba, F. S. (2012). Enhanced Genetic Algorithm Based on Node Codes for Mobile Robot Path Planning. Iraqi Journal of Computer Communication and Control Engineering, 12(2), 69–80.
  Google Scholar

Mustafa, O., Yousif, A., & Abdulqadir, D. (2019). Improving Error Correction Stage and Expanding the Final Key using Dynamic Linear-feedback Shift Register in Sarg04 Protocol. Polytechnic Journal, 9(1), 1–6.
DOI: https://doi.org/10.25156/ptj.v9n1y2019.pp1-6   Google Scholar

Schwartz, C. (1998). Web search engines. Journal of the American Society for Information Science, 49(11), 973–982. https://doi.org/10.1002/(SICI)1097-4571(1998)49:11<973::AID-ASI3>3.0.CO;2-Z
DOI: https://doi.org/10.1002/(SICI)1097-4571(1998)49:11<973::AID-ASI3>3.0.CO;2-Z   Google Scholar

Smith, J. (2010). Be 1 on Google: 52 fast and easy search engine optimization tools to drive customers to your web site. McGraw-Hill.
  Google Scholar

Thelwall, M. (2015). Web crawlers and search engines. In Jens-Erik, Link analysis: An information science approach. Emerald Group Publishing Limited.
  Google Scholar

UKEssays. (November 2018). Literature Review on “The Concept of Search Engine Optimization. Retrieved from https://www.ukessays.com/essays/marketing/the-concept-of-search-engine-optimization-and-its-innovations-marketing-essay.php?vref=1
  Google Scholar

Xu, L., Chen, J., & Whinston, A. (2012). Effects of the presence of organic listing in search advertising. Information Systems Research, 23(4), 1284–1302.
DOI: https://doi.org/10.1287/isre.1120.0425   Google Scholar

Yang, S., & Ghose, A. (2010). Analyzing the relationship between organic and sponsored search advertising: Positive, negative, or zero interdependence. Marketing Science, 29(4), 602–623.
DOI: https://doi.org/10.1287/mksc.1090.0552   Google Scholar

Zhang, S., & Cabage, N. (2016). Search engine optimization: Comparison of link building and social sharing. Journal of Computer Information Systems, 57(2), 148–159. https://doi.org/10.1080/08874417.2016.1183447
DOI: https://doi.org/10.1080/08874417.2016.1183447   Google Scholar

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Published
2021-03-30

Cited by

ALMUKHTAR, F., MAHMOODD, N., & KAREEM, S. (2021). SEARCH ENGINE OPTIMIZATION: A REVIEW. Applied Computer Science, 17(1), 70–80. https://doi.org/10.23743/acs-2021-07

Authors

Firas ALMUKHTAR 

Imam Jaafar Al-Sadiq University Iraq

Authors

Nawzad MAHMOODD 

Erbil Polytechnic University, Information System Engineering Iraq

Authors

Shahab KAREEM 
shahabwk@yahoo.com
Erbil Polytechnic University, Information System Engineering Iraq

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