Explicit factor models for explainable recommendation based on phrase-level sentiment analysis

Y Zhang, G Lai, M Zhang, Y Zhang, Y Liu… - Proceedings of the 37th …, 2014 - dl.acm.org
Collaborative Filtering (CF)-based recommendation algorithms, such as Latent Factor
Models (LFM), work well in terms of prediction accuracy. However, the latent features make it …
被引用次数：1005 相关文章

Explicit Factor Models for explainable recommendation based on phrase-level sentiment analysis

Y Zhang, G Lai, M Zhang, Y Zhang… - … on Research and …, 2014 - researchwithrutgers.com
Collaborative Filtering (CF)-based recommendation algorithms, such as Latent Factor
Models (LFM), work well in terms of prediction accuracy. However, the latent features make it …
[PDF] thuir.cn

[PDF][PDF] Explicit Factor Models for Explainable Recommendation based on Phrase-level Sentiment Analysis

Y Zhang, G Lai, M Zhang, Y Zhang, Y Liu, S Ma - 2014 - thuir.cn
Collaborative Filtering (CF)-based recommendation algorithms, such as Latent Factor
Models (LFM), work well in terms of prediction accuracy. However, the latent features make it …
[PDF] researchgate.net

[PDF][PDF] Explicit Factor Models for Explainable Recommendation based on Phrase-level Sentiment Analysis

Y Zhang, G Lai, M Zhang, Y Zhang, Y Liu, S Ma - 2014 - researchgate.net
Collaborative Filtering (CF)-based recommendation algorithms, such as Latent Factor
Models (LFM), work well in terms of prediction accuracy. However, the latent features make it …
[PDF] yongfeng.me

[PDF][PDF] Explicit Factor Models for Explainable Recommendation based on Phrase-level Sentiment Analysis

Y Zhang, G Lai, M Zhang, Y Zhang, Y Liu, S Ma - 2014 - yongfeng.me
Collaborative Filtering (CF)-based recommendation algorithms, such as Latent Factor
Models (LFM), work well in terms of prediction accuracy. However, the latent features make it …

[引用][C] Explicit factor models for explainable recommendation based on phrase-level sentiment analysis

Y Zhang, G Lai, M Zhang, Y Zhang, Y Liu… - Proceedings of the 37th …, 2014 - cir.nii.ac.jp
Explicit factor models for explainable recommendation based on phrase-level sentiment
analysis | CiNii Research CiNii 国立情報学研究所 学術情報ナビゲータ[サイニィ] 詳細へ移動 検索 …
[PDF] archive.org

[PDF][PDF] Explicit Factor Models for Explainable Recommendation based on Phrase-level Sentiment Analysis

Y Zhang, G Lai, M Zhang, Y Zhang, Y Liu, S Ma - 2014 - scholar.archive.org
Collaborative Filtering (CF)-based recommendation algorithms, such as Latent Factor
Models (LFM), work well in terms of prediction accuracy. However, the latent features make it …
[PDF] thuir.org

[PDF][PDF] Explicit Factor Models for Explainable Recommendation based on Phrase-level Sentiment Analysis

Y Zhang, G Lai, M Zhang, Y Zhang, Y Liu, S Ma - 2014 - thuir.org
Collaborative Filtering (CF)-based recommendation algorithms, such as Latent Factor
Models (LFM), work well in terms of prediction accuracy. However, the latent features make it …
[PDF] cmu.edu

[PDF][PDF] Explicit Factor Models for Explainable Recommendation based on Phrase-level Sentiment Analysis

Y Zhang, G Lai, M Zhang, Y Zhang, Y Liu, S Ma - 2014 - cs.cmu.edu
Collaborative Filtering (CF)-based recommendation algorithms, such as Latent Factor
Models (LFM), work well in terms of prediction accuracy. However, the latent features make it …
[PDF] academia.edu

[PDF][PDF] Explicit Factor Models for Explainable Recommendation based on Phrase-level Sentiment Analysis

Y Zhang, G Lai, M Zhang, Y Zhang, Y Liu, S Ma - 2014 - academia.edu
Collaborative Filtering (CF)-based recommendation algorithms, such as Latent Factor
Models (LFM), work well in terms of prediction accuracy. However, the latent features make it …