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A Survey on the Use of Personalized Model-Based Search Engine

EasyChair Preprint no. 5400

10 pagesDate: April 28, 2021


With the development of the information industry, especially the Internet and Mobile Internet, the amount of information that we have to deal with is rapidly growing. To some extent, people can get any information they want from the Internet. In the face of such tremendous information availability and explosion, people need an effective way to find only the interesting and relevant information. How to enhance user experience during the process of searching for information is yet to be resolved. Searching has been the main function of a traditional search engine. There has not been enough personalization being built-in search engines for searchers to use during the process of information search and retrieval. This paper, therefore, studied and explored the personalization of searches by using a personalized model that supports search engines. We present a general review of the literature on search engine personalization for web based searches. The survey is partly systematic, and at the end of the review, we present the challenges faced in personalizing search engines.

Keyphrases: Information Retrieval, Model-Based Search Engine, personalized search engine, search engine

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Mohammed Mahdi and Abdul Ahmad and Qais Saif Qassim and Mohammed Ahmed Subhi and Taofiq Adeola Bakare},
  title = {A Survey on the Use of Personalized Model-Based Search Engine},
  howpublished = {EasyChair Preprint no. 5400},

  year = {EasyChair, 2021}}
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