{"title":"PNCF:基于预训练嵌入的神经协同过滤","authors":"Jianqi Pan, M. Yamamura, Atsushi Yoshikawa","doi":"10.1117/12.2639163","DOIUrl":null,"url":null,"abstract":"In this paper, we propose the recommendation algorithm PNCF for neural networks. We designed a pre-training task for a distributed representation of embeddings based on many-to-many information. We used the word2vec technique in natural language processing to implement the embedding of users and items. We also constructed a brand-new video website tagauthor pre-training dataset. The code in this paper was implemented in PyTorch and is publicly available on GitHub (github.com/jannchie/ PNCF).","PeriodicalId":336892,"journal":{"name":"Neural Networks, Information and Communication Engineering","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"PNCF: neural collaborative filtering based on pre-trained embedding\",\"authors\":\"Jianqi Pan, M. Yamamura, Atsushi Yoshikawa\",\"doi\":\"10.1117/12.2639163\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose the recommendation algorithm PNCF for neural networks. We designed a pre-training task for a distributed representation of embeddings based on many-to-many information. We used the word2vec technique in natural language processing to implement the embedding of users and items. We also constructed a brand-new video website tagauthor pre-training dataset. The code in this paper was implemented in PyTorch and is publicly available on GitHub (github.com/jannchie/ PNCF).\",\"PeriodicalId\":336892,\"journal\":{\"name\":\"Neural Networks, Information and Communication Engineering\",\"volume\":\"61 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neural Networks, Information and Communication Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2639163\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neural Networks, Information and Communication Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2639163","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
PNCF: neural collaborative filtering based on pre-trained embedding
In this paper, we propose the recommendation algorithm PNCF for neural networks. We designed a pre-training task for a distributed representation of embeddings based on many-to-many information. We used the word2vec technique in natural language processing to implement the embedding of users and items. We also constructed a brand-new video website tagauthor pre-training dataset. The code in this paper was implemented in PyTorch and is publicly available on GitHub (github.com/jannchie/ PNCF).
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