DEMYSTIFYING SEARCH INDEXING AND RANKING

This article explores the intricate processes of search indexing and ranking, which form the backbone of modern search engine technology. It traces the evolution of search engine performance from 2010 to 2022, highlighting significant improvements in web page indexing, search speed, and user satisfaction. The article delves into the key components of search indexing, including content crawling, analysis, index creation, and maintenance, emphasizing recent advancements in natural language processing and machine learning. It then examines search ranking algorithms, discussing crucial factors such as content relevance, authority, user intent, and personalization. The study also investigates emerging trends in search technology, including the impact of mobile and voice search, the growing importance of user experience metrics, and the shift towards entity-based and AI-driven search capabilities. By providing a detailed analysis of these interconnected processes, this article offers valuable insights into the current state and future direction of search technology, underscoring its pivotal role in organizing and accessing the vast landscape of digital information in an increasingly connected world.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-10-15
DOI
https://doi.org/10.5281/zenodo.13934942
Primary Topic
Information Retrieval and Search Behavior
Type
article
Field-Weighted Citation Impact
0.00
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article

DEMYSTIFYING SEARCH INDEXING AND RANKING

Zenodo (CERN European Organization for Nuclear Research)
Information Retrieval and Search Behavior
article

DEMYSTIFYING SEARCH INDEXING AND RANKING

article en

Abstract

This article explores the intricate processes of search indexing and ranking, which form the backbone of modern search engine technology. It traces the evolution of search engine performance from 2010 to 2022, highlighting significant improvements in web page indexing, search speed, and user satisfaction. The article delves into the key components of search indexing, including content crawling, analysis, index creation, and maintenance, emphasizing recent advancements in natural language processing and machine learning. It then examines search ranking algorithms, discussing crucial factors such as content relevance, authority, user intent, and personalization. The study also investigates emerging trends in search technology, including the impact of mobile and voice search, the growing importance of user experience metrics, and the shift towards entity-based and AI-driven search capabilities. By providing a detailed analysis of these interconnected processes, this article offers valuable insights into the current state and future direction of search technology, underscoring its pivotal role in organizing and accessing the vast landscape of digital information in an increasingly connected world.

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 46%
Information Retrieval and Search Behavior
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DEMYSTIFYING SEARCH INDEXING AND RANKING · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS