TY  - JOUR
T1  - Keyword-Based Collaborative Filter Recommendation System Using Scraping
AU - Joon Kim, Jeong AU - Jun Kim, Young AU - Min Park, Jeong AU - Taek Chung, Sung 
JO  - Journal of Engineering and Applied Sciences
VL  - 13
IS  - 6
SP  - 1506
EP  - 1514
PY  - 2018
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2018.1506.1514
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2018.1506.1514
KW  - Collaboration filter
KW  -recommendation system
KW  -scraping
KW  -movie recommend
KW  -keyword-based
KW  -purchase
AB  - CF (Collaborative Filtering) is one of the methods generally utilized in recommendation system. The
goal of CF is to analyze the purchase trend of other customers similar to a target customer and recommend items
that can be preferred by the customer among the items he or she has not bought. Conventional CF, however
is hardly capable of predicting any new customer’s purchase trend for they have no existing purchase list. To
resolve the problem, it surveys customers too much or changes items into profile, causing huge expenses and
difficulty. In this study, as a new method to solve such a problem, keyword-based collaborative filter
recommendation system using scraping is proposed.
ER  -