C语言版协同过滤算法,Recommender:使用协同过滤进行产品推荐/建议的C语言库

RecommenderAC是一款采用协同过滤技术的产品推荐库,支持用户和物品为基础的推荐方式。该库无需外部依赖,运行速度快,在10百万条评分数据上仅需约81秒,并且内存占用少于160MB。适用于快速构建推荐系统的场景。

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A C library for product recommendations/suggestions using collaborative filtering (CF).

Recommender analyzes the feedback of some users (implicit and explicit) and their preferences for some items. It learns patterns and predicts the most suitable products for a particular user.

Features

Collaborative Filtering

User and Item based recommenders

No external dependencies

Fast running time ~ 81 seconds for 10 million ratings (on MovieLens Data Sets)

Memory footprint under 160 MB for 10 million ratings

Webpage

Building

To compile Recommender:

make

The compilation will produce libRecommender.a

To compile an example:

gcc test/test.c src/libRecommender.a -lm -o test/t1 -I src/

Alternatively you can use clang

clang test/test.c src/libRecommender.a -lm -o test/t1 -I src/

Keywords

Collaborative filtering, recommender system

References

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