Implement the Item-based Recommendation Algorithm and calculate the similarity of users and items.
Notice : I'm sorry about that it is not efficient enough in this recommendation engine when calculating the similarity matrix and computing the prediction matrix. I have optimized this problem and the code will be shared soon.
- Item-based Recommendation Algorithm is the most commomly used algorithm in Recommendation System, you can refer to 《Mahout in Action》Chapter1.6 “Distributing recommendation computations” for more details.
- I calculated the Item-Similarity and User-Similarity by reading paper “Empirical Analysis of Predictive Algorithms for Collaborative Filtering”, by John S.Breese.
- I also implement a CRON for RecommendEngine so that the recently-records can be fetched from MySQL to HDFS and after accomplish the computation tasks, the recommended result will be loaded into MySQL periodically.
- I got MovieLens DataSets from here.
- Ubuntu 14.04
- JDK 1.7.0_75
- Hadoop 1.2.1
- Sqoop 1.3.0
- Email: tinylcy@yeah.net or tinylcy@gmail.com
- Sina Weibo: @tinylcy