Start Date
10-17-2017 10:00 AM
Description
With the emergence of E‐commerce, recommendation system becomes a significant tool which can help both sellers and buyers. It helps sellers by increasing the profits and advertising items to customers. In addition, recommendation systems facilitate buyers to find items they are looking for easily.
In recommendation systems, the rating matrix R represents users' ratings for items. The rows in the rating matrix represent the users and the columns represent items. If particular user rates a particular item, then the value of the intersection of the user row and item column holds the rating value. The trust matrix T describes the trust relationship between users. The rows hold the users who create a trust relationship ‐ trustor ‐ and the columns represent users who have been trusted by trustors ‐ trustee ‐.
Included in
Imputing Trust Network Information in NMF‐based Recommendation Systems
With the emergence of E‐commerce, recommendation system becomes a significant tool which can help both sellers and buyers. It helps sellers by increasing the profits and advertising items to customers. In addition, recommendation systems facilitate buyers to find items they are looking for easily.
In recommendation systems, the rating matrix R represents users' ratings for items. The rows in the rating matrix represent the users and the columns represent items. If particular user rates a particular item, then the value of the intersection of the user row and item column holds the rating value. The trust matrix T describes the trust relationship between users. The rows hold the users who create a trust relationship ‐ trustor ‐ and the columns represent users who have been trusted by trustors ‐ trustee ‐.
