Application of k-means clustering algorithm to improve effectiveness of the results recommended by journal recommender system

This study investigates to evaluate feasibility of k-means clustering algorithm in order to improve effectiveness of the results recommended by RICEST Journal Finder System. More than 15,000 papers published in filed of engineering journals during 2013–2017 were collected from their websites. Their...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Scientometrics Ročník 127; číslo 6; s. 3237 - 3252
Hlavní autoři:	Vara, Narjes, Mirzabeigi, Mahdieh, Sotudeh, Hajar, Fakhrahmad, Seyed Mostafa
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Cham Springer International Publishing 01.06.2022 Springer Nature B.V
Témata:	Algorithms Attitudes Cluster analysis Clustering Computer Science Effectiveness Feasibility Feasibility studies Information Storage and Retrieval Library Science Recommender systems System effectiveness Vector quantization Websites Journal recommender systems k-means clustering algorithm RICeST journal finder system Effectiveness Scalability
ISSN:	0138-9130, 1588-2861
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!