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A Multidimensional Comparison of Search Engines and Chatgpt in Terms of Information Needs


Article Information

Title: A Multidimensional Comparison of Search Engines and Chatgpt in Terms of Information Needs

Authors: Umar Khattab, Sarah Bukhari, Ayesha Khan, Abubakar Kamal

Journal: Journal of Computing & Biomedical Informatics

HEC Recognition History
Category From To
Y 2023-07-01 2024-09-30
Y 2022-07-01 2023-06-30

Publisher: Research Center of Computing & Biomedical Informatics

Country: Pakistan

Year: 2025

Volume: 9

Issue: 1

Language: en

Keywords: InternetprecisionRecallsearch engineRelevant Retrieval Result

Categories

Abstract

Search engines are an important tool for accessing information today. However, it isn't easy to understand how they process different types of information needs, such as General, Navigational, and Transactional and how their results are relevant to each other. This research compares four widely used search engines such as Google, Bing, DuckDuckGo, and Brave along with a most popular AI tool ChatGPT. The primary objective is to evaluate how effectively these platforms fulfil various information needs. Each search engine and ChatGPT was tested using the same questions to compare how well they work. Their performance was checked based on a few important things like relevance, accuracy, speed, precision, recall and user privacy. Traditional search engines like Google and Bing use keywords meaning they look for exact words the user types. On the other side, ChatGPT is an AI tool that understands natural   language and gives answers based on the meaning and context of the question, not just the exact words. The results from all platforms were divided into two types relevant and irrelevant. These results were shown that each search engine and AI tool has strengths and weaknesses. Google and Bing provided accurate answers, Brave and DuckDuckGo delivered faster results, while DuckDuckGo and ChatGPT offered better user privacy protection. This research also highlights the challenge of understanding how various platforms address different information needs. This study helps improve search technologies to make users more satisfied, improve accuracy, and make information retrieval more efficient.


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