品牌內容發現(二)Learning Visual Elements of Images for Discovery of Brand Posts
背景 之前講到過，品牌內容發現(content discovery for brands)這一問題被定性爲基於內容的排序學習問題。 這種利用品牌的歷史post來學習其與品牌的相關性從而對新的post進行排名的任務，主要難點有三： （1）品牌之間的相似性問題。多個品牌可能使用相同的品牌聯想內容，導致本品牌的post與競爭對手使用的post僅有細微差別，難以區分 （2）brand-post之間的稀疏性
相關文章
- 1. 品牌內容發現(二)Learning Subjective Attributes of Images from Auxiliary Sources
- 2. On the burstiness of visual elements
- 3. 讀The Elements of Statistical learning
- 4. A Simple Framework for Contrastive Learning of Visual Representations
- 5. Learning like a Child: Fast Novel Visual Concept Learning from Sentence Descriptions of Images
- 6. Deep Clustering for Unspervised Learning of Visual Features
- 7. [解讀] Deep Clustering for Unsupervised Learning of Visual Features
- 8. Visual Analysis of Discrimination in Machine Learning
- 9. 2017CVPRSelf-Supervised Learning of Visual Features Through Embedding Images Into Text Topic Spaces
- 10. Vulnerability Extrapolation: Assisted Discovery of Vulnerabilities using Machine Learning
- 更多相關文章...
- • XSLT
- • XSLT
- • Spring Cloud 微服務實戰(三) - 服務註冊與發現
- • PHP開發工具
相關標籤/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
最新文章
歡迎關注本站公眾號,獲取更多信息
相關文章
- 1. 品牌內容發現(二)Learning Subjective Attributes of Images from Auxiliary Sources
- 2. On the burstiness of visual elements
- 3. 讀The Elements of Statistical learning
- 4. A Simple Framework for Contrastive Learning of Visual Representations
- 5. Learning like a Child: Fast Novel Visual Concept Learning from Sentence Descriptions of Images
- 6. Deep Clustering for Unspervised Learning of Visual Features
- 7. [解讀] Deep Clustering for Unsupervised Learning of Visual Features
- 8. Visual Analysis of Discrimination in Machine Learning
- 9. 2017CVPRSelf-Supervised Learning of Visual Features Through Embedding Images Into Text Topic Spaces
- 10. Vulnerability Extrapolation: Assisted Discovery of Vulnerabilities using Machine Learning