Comparative analysis: recommendation techniques in e-commerce

Waleed Ibrahim; Binaya Subedi; Sabreena Zoha; Abdussalam Ali; Emran Salahuddin

doi:10.1007/978-3-031-33743-7_8

Comparative analysis: recommendation techniques in e-commerce

Waleed Ibrahim, Binaya Subedi, Sabreena Zoha, Abdussalam Ali, Emran Salahuddin

Western Sydney University

Research output: Chapter in Book / Conference Paper › Chapter › peer-review

Abstract

Recommendation systems have become more vital in addressing the current state of information overload in e-commerce. It assists in filtering data according to customer's personal interests. This research did comparative analysis on 30 papers that developed recommendation systems, and the techniques they utilized to generate customised and personalised data according to the customer needs. Then it proposed a new model considering the shortcoming of the analysed systems. It incorporates the nature of the data whether implicit and explicit, Recommendations techniques, and view of the data to provide recommendations that can assist e-commerce businesses to provide the products and services that better suits the customers' customized and personalised preferences from enormous amount of collected data.

Original language	English
Title of host publication	Proceedings of the 2023 International Conference on Advances in Computing Research (ACR’23)
Editors	Kevin Daimi, Abeer Al Sadoon
Place of Publication	Switzerland
Publisher	Springer
Pages	96-107
Number of pages	12
ISBN (Electronic)	9783031337437
ISBN (Print)	9783031337420
DOIs	https://doi.org/10.1007/978-3-031-33743-7_8
Publication status	Published - 2023
Event	International Conference on Advances in Computing Research - Orlando, United States Duration: 8 May 2023 → 10 May 2023 Conference number: 1st

Publication series

Name	Lecture Notes in Networks and Systems
Volume	700 LNNS
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	International Conference on Advances in Computing Research
Country/Territory	United States
City	Orlando
Period	8/05/23 → 10/05/23

Keywords

Collaborative filtering
Data sources
E-Commerce
Personalization
Recommendation system

Access to Document

10.1007/978-3-031-33743-7_8

Cite this

Ibrahim, W., Subedi, B., Zoha, S., Ali, A., & Salahuddin, E. (2023). Comparative analysis: recommendation techniques in e-commerce. In K. Daimi, & A. Al Sadoon (Eds.), Proceedings of the 2023 International Conference on Advances in Computing Research (ACR’23) (pp. 96-107). (Lecture Notes in Networks and Systems; Vol. 700 LNNS). Springer. https://doi.org/10.1007/978-3-031-33743-7_8

@inbook{995df957f37b45dd8c462f5080de53a9,

title = "Comparative analysis: recommendation techniques in e-commerce",

abstract = "Recommendation systems have become more vital in addressing the current state of information overload in e-commerce. It assists in filtering data according to customer's personal interests. This research did comparative analysis on 30 papers that developed recommendation systems, and the techniques they utilized to generate customised and personalised data according to the customer needs. Then it proposed a new model considering the shortcoming of the analysed systems. It incorporates the nature of the data whether implicit and explicit, Recommendations techniques, and view of the data to provide recommendations that can assist e-commerce businesses to provide the products and services that better suits the customers' customized and personalised preferences from enormous amount of collected data.",

keywords = "Collaborative filtering, Data sources, E-Commerce, Personalization, Recommendation system",

author = "Waleed Ibrahim and Binaya Subedi and Sabreena Zoha and Abdussalam Ali and Emran Salahuddin",

year = "2023",

doi = "10.1007/978-3-031-33743-7_8",

language = "English",

isbn = "9783031337420",

series = "Lecture Notes in Networks and Systems",

publisher = "Springer",

pages = "96--107",

editor = "Kevin Daimi and {Al Sadoon}, Abeer",

booktitle = "Proceedings of the 2023 International Conference on Advances in Computing Research (ACR{\textquoteright}23)",

note = "International Conference on Advances in Computing Research ; Conference date: 08-05-2023 Through 10-05-2023",

}

Ibrahim, W, Subedi, B, Zoha, S, Ali, A & Salahuddin, E 2023, Comparative analysis: recommendation techniques in e-commerce. in K Daimi & A Al Sadoon (eds), Proceedings of the 2023 International Conference on Advances in Computing Research (ACR’23). Lecture Notes in Networks and Systems, vol. 700 LNNS, Springer, Switzerland, pp. 96-107, International Conference on Advances in Computing Research, Orlando, Florida, United States, 8/05/23. https://doi.org/10.1007/978-3-031-33743-7_8

Comparative analysis: recommendation techniques in e-commerce. / Ibrahim, Waleed; Subedi, Binaya; Zoha, Sabreena et al.
Proceedings of the 2023 International Conference on Advances in Computing Research (ACR’23). ed. / Kevin Daimi; Abeer Al Sadoon. Switzerland: Springer, 2023. p. 96-107 (Lecture Notes in Networks and Systems; Vol. 700 LNNS).

Research output: Chapter in Book / Conference Paper › Chapter › peer-review

TY - CHAP

T1 - Comparative analysis: recommendation techniques in e-commerce

AU - Ibrahim, Waleed

AU - Subedi, Binaya

AU - Zoha, Sabreena

AU - Ali, Abdussalam

AU - Salahuddin, Emran

N1 - Conference code: 1st

PY - 2023

Y1 - 2023

N2 - Recommendation systems have become more vital in addressing the current state of information overload in e-commerce. It assists in filtering data according to customer's personal interests. This research did comparative analysis on 30 papers that developed recommendation systems, and the techniques they utilized to generate customised and personalised data according to the customer needs. Then it proposed a new model considering the shortcoming of the analysed systems. It incorporates the nature of the data whether implicit and explicit, Recommendations techniques, and view of the data to provide recommendations that can assist e-commerce businesses to provide the products and services that better suits the customers' customized and personalised preferences from enormous amount of collected data.

AB - Recommendation systems have become more vital in addressing the current state of information overload in e-commerce. It assists in filtering data according to customer's personal interests. This research did comparative analysis on 30 papers that developed recommendation systems, and the techniques they utilized to generate customised and personalised data according to the customer needs. Then it proposed a new model considering the shortcoming of the analysed systems. It incorporates the nature of the data whether implicit and explicit, Recommendations techniques, and view of the data to provide recommendations that can assist e-commerce businesses to provide the products and services that better suits the customers' customized and personalised preferences from enormous amount of collected data.

KW - Collaborative filtering

KW - Data sources

KW - E-Commerce

KW - Personalization

KW - Recommendation system

UR - http://www.scopus.com/inward/record.url?scp=85163407011&partnerID=8YFLogxK

UR - https://go.openathens.net/redirector/westernsydney.edu.au?url=https://doi.org/10.1007/978-3-031-33743-7_8

U2 - 10.1007/978-3-031-33743-7_8

DO - 10.1007/978-3-031-33743-7_8

M3 - Chapter

AN - SCOPUS:85163407011

SN - 9783031337420

T3 - Lecture Notes in Networks and Systems

SP - 96

EP - 107

BT - Proceedings of the 2023 International Conference on Advances in Computing Research (ACR’23)

A2 - Daimi, Kevin

A2 - Al Sadoon, Abeer

PB - Springer

CY - Switzerland

T2 - International Conference on Advances in Computing Research

Y2 - 8 May 2023 through 10 May 2023

ER -

Comparative analysis: recommendation techniques in e-commerce

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this