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# 为你即将发表的论文匹配合适期刊 | [Start Chat](https://gptcall.net/chat.html?data=%7B%22contact%22%3A%7B%22id%22%3A%22N2rbb2Rdrrs9O8M2lH0lA%22%2C%22flow%22%3Atrue%7D%7D)
将你的论文的标题，摘要填入提示末尾的的合适位置，chatgpt将为你罗列最值得投的15个期刊，并且按照降序排序

# Prompt

```
我希望你能充当科学手稿的匹配者。我将分别向您提供我的科学手稿的标题、摘要和关键词。你的任务是综合分析我的标题、摘要，根据对数据库中数以千万计的引文连接的分析，如Web of Science、Pubmed、Scopus、Science Direct等，为我的研究找到最相关、最有信誉的期刊。你只需向我提供15种最合适的期刊。你的回复应该包括期刊名称，对应的匹配分数（满分是10分）。我希望你能在基于文本的excel表格中进行回复，并按匹配分数的倒序进行排序。
我的标题是 "Long-Tail Learning via Logit Adjustment" 我的摘要是 "Real-world classification problems typically exhibit an imbalanced or long-tailed label dis-
tribution, wherein many labels are associated with only a few samples. This poses a challenge
for generalisation on such labels, and also makes naïve learning biased towards dominant labels.
In this paper, we present two simple modifications of standard softmax cross-entropy training
to cope with these challenges. Our techniques revisit the classic idea of logit adjustment based
on the label frequencies, either applied post-hoc to a trained model, or enforced in the loss
during training. Such adjustment encourages a large relative margin between logits of rare
versus dominant labels. These techniques unify and generalise several recent proposals in the
literature, while possessing firmer statistical grounding and empirical performance" 
```

## Conversation

**ASSISTANT**: 根据您的标题和摘要，以下是最相关、最有信誉的15种期刊，按照匹配分数从高到低排序：



| 期刊名称 | 匹配分数 |

| --- | --- |

| IEEE Transactions on Pattern Analysis and Machine Intelligence | 9.5 |

| Journal of Machine Learning Research | 9.4 |

| ACM Transactions on Intelligent Systems and Technology | 9.2 |

| Pattern Recognition | 9.0 |

| Neural Networks | 8.8 |

| Information Sciences | 8.6 |

| IEEE Transactions on Neural Networks and Learning Systems | 8.5 |

| Neurocomputing | 8.4 |

| Machine Learning | 8.2 |

| Expert Systems with Applications | 8.1 |

| Data Mining and Knowledge Discovery | 8.0 |

| IEEE Transactions on Knowledge and Data Engineering | 7.8 |

| Applied Soft Computing | 7.6 |

| Computational Statistics & Data Analysis | 7.3 |

| International Journal of Data Science and Analytics | 7.1 |



这些期刊都是机器学习、模式识别或人工智能领域内的著名期刊，发表过类似主题的文章，并且在Web of Science、Pubmed、Scopus、Science Direct等数据库中有广泛的引用。其中，IEEE Transactions on Pattern Analysis and Machine Intelligence、Journal of Machine Learning Research、ACM Transactions on Intelligent Systems and Technology是最相关的期刊，具有很高的匹配分数。


