Product Recommendations in E-commerce Systems using Content-based Clustering and Collaborative Filtering
(2015) FMS820 20152Mathematical Statistics
- Abstract
- In this report we take a new approach to product recommendation. We investigate
the the possibility of using a hybrid recommender consisting of contentbased
clustering and connections between clusters using collaborative filtering
to make good product recommendations.
The algorithm is tested on real product and purchase data from two different
companies - a big online book store and a smaller online clothing store.
It is evaluated both for functionality as a backfiller to other algorithms and as
a strong individual algorithm. The evaluation mainly looks at the number of
purchases as metric but also uses accuracy and recall as evaluation metrics.
The algorithm shows some promise for using it as an individual algorithm.
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/7860347
- author
- Hansson, Linda
- supervisor
- organization
- course
- FMS820 20152
- year
- 2015
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- Collaborative filtering, Content-based clustering, Recommender systems
- language
- English
- id
- 7860347
- date added to LUP
- 2015-09-07 16:14:08
- date last changed
- 2015-09-08 11:26:39
@misc{7860347, abstract = {{In this report we take a new approach to product recommendation. We investigate the the possibility of using a hybrid recommender consisting of contentbased clustering and connections between clusters using collaborative filtering to make good product recommendations. The algorithm is tested on real product and purchase data from two different companies - a big online book store and a smaller online clothing store. It is evaluated both for functionality as a backfiller to other algorithms and as a strong individual algorithm. The evaluation mainly looks at the number of purchases as metric but also uses accuracy and recall as evaluation metrics. The algorithm shows some promise for using it as an individual algorithm.}}, author = {{Hansson, Linda}}, language = {{eng}}, note = {{Student Paper}}, title = {{Product Recommendations in E-commerce Systems using Content-based Clustering and Collaborative Filtering}}, year = {{2015}}, }