Collaborative Filtering Based Recommender Systems For Marketplace Applications
DOI:
https://doi.org/10.51601/ijersc.v2i5.184Abstract
The background of this research is to give the best advice to users
who still don't know about other marketplaces that they can still
use, to find the items they are looking for and at a cheaper price or
with promos they can get. The method used in this research is to
use a trial based on data obtained from users who use the media
marketplace to purchase an item, with this, the real data can be
known so that the best advice for an unknown marketplace can be
given. In how many countries, a recommender system has been
implemented in a marketplace that will provide advice using
advertising media on social media, by using social media, users
can find out about the marketplace, and are given continuous
advice to install the application so that they can make transactions
with purchase of a product in the marketplace. The purpose of this
research is to give the best advice so that all people, especially
marketplace users, can find out which other marketplaces are in
order to know and be able to shop at other marketplaces, by doing
price comparisons and being able to get promo prices and knowing
based on habits, and ratings from the marketplace.
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