Evidence map›Paper›PMID 38854703›Full record

ArticleF1000Research2023

Search engine Performance optimization: methods and techniques.

Serge Stephane Aman, Behou Gerard N'guessan, Djama Djoman Alfred Agbo, Tiemoman Kone

Abstract read
In one paragraph

Article in F1000Research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Serge Stephane AmanUniversite Virtuelle de Cote d'Ivoire, Abidjan, Lagunes Region, 225, Cote d'Ivoire.ORCID https://orcid.org/0000-0002-7922-2444
Behou Gerard N'guessanUniversite Virtuelle de Cote d'Ivoire, Abidjan, Lagunes Region, 225, Cote d'Ivoire.ORCID https://orcid.org/0000-0001-6007-1933
Djama Djoman Alfred AgboUniversite Felix Houphouet-Boigny, Abidjan, Lagunes Region, 225, Cote d'Ivoire.
Tiemoman KoneUniversite Virtuelle de Cote d'Ivoire, Abidjan, Lagunes Region, 225, Cote d'Ivoire.ORCID https://orcid.org/0009-0007-1323-8578

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: With the rapid advancement of information technology, search engine optimisation (SEO) has become crucial for enhancing the visibility and relevance of online content. In this context, the use of cloud platforms like Microsoft Azure is being explored to bolster SEO capabilities. Methods: This scientific article offers an in-depth study of search engine optimisation. It explores the different methods and techniques used to improve the performance and efficiency of a search engine, focusing on key aspects such as result relevance, search speed and user experience. The article also presents case studies and concrete examples to illustrate the practical application of optimisation techniques. Results: The results demonstrate the importance of optimisation in delivering high quality search results and meeting the increasing demands of users. Conclusions: The article addresses the enhancement of search engines through the Microsoft Azure infrastructure and its associated components. It highlights methods such as indexing, semantic analysis, parallel searches, and caching to strengthen the relevance of results, speed up searches, and optimise the user experience. Following the application of these methods, a marked improvement was observed in these areas, thereby showcasing the capability of Microsoft Azure in enhancing search engines. The study sheds light on the implementation and analysis of these Azure-focused techniques, introduces a methodology for assessing their efficacy, and details the specific benefits of each method. Looking forward, the article suggests integrating artificial intelligence to elevate the relevance of results, venturing into other cloud infrastructures to boost performance, and evaluating these methods in specific scenarios, such as multimedia information search. In summary, with Microsoft Azure, the enhancement of search engines appears promising, with increased relevance and a heightened user experience in a rapidly evolving sector.

Indexed as

architecturefull-cloudon-premise data centreSearch engine

Identifiers

PMID38854703
PMCPMC11157186

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.