earticle

영어

This study proposes a content-based recommendation algorithm (NRA) for pet food. The proposed algorithm tries to recommend appropriate or inappropriate feed by using collective intelligence based on user experience and prior knowledge of experts. Based on the physical and health status of the dogs, this study suggests what kind of nutrients are necessary for the dogs and the most recommended pet food containing these nutrients. Performance evaluation was performed in terms of recall, precision, F1 and AUC. As a result of the performance evaluation, the AUC and F1 value of the proposed NRA was 15% and 42% higher than that of the baseline model, respectively. In addition, the performance of NRA is shown higher for recommendation of normal dogs than disease dogs.