地球资源数据云——数据资源详情
NLP 研究文章
该数据集《NLP on Research Articles》主要用于多分类任务，数据形态以文本为主，应用场景偏向金融风控。 题目说明：Multi Label Classification using NLP on Research Articles 任务类型：文本多分类。 建议流程：先做文本清洗与分词，再比较 TF - IDF+线性模型 与 预训练语言模型。 评估建议：使用分层切分或交叉验证，优先关注 F1、Recall、AUC 等分类指标。 可用文件：sample_submission.csv, test.csv, train.csv。 Context Topic Modeling for Research Articles Researchers have access to large online archives of scientific articles. As a consequence, finding relevant articles has become more difficult. Tagging or topic modelling provides a way to give token of identification to research articles which facilitates recommendation and search process. Content Given the abstract and title for a set of research articles, predict the topics for each article included in the test set. Note that a research article can possibly have more than 1 topic. The research article abstracts and titles are sourced from the following 6 topics:
摘要概览
该数据集《NLP on Research Articles》主要用于多分类任务，数据形态以文本为主，应用场景偏向金融风控。 题目说明：Multi Label Classification using NLP on Research Articles
任务类型：文本多分类。
建议流程：先做文本清洗与分词，再比较 TF - IDF+线性模型 与 预训练语言模型。
评估建议：使用分层切分或交叉验证，优先关注 F1、Recall、AUC 等分类指标。
可用文件：sample_submission.csv, test.csv, train.csv。
Context
Topic Modeling for Research Articles Researchers have access to large online archives of scientific articles. As a consequence, finding relevant articles has become more difficult. Tagging or topic modelling provides a way to give token of identification to research articles which facilitates recommendation and search process.
Content
Given the abstract and title for a set of research articles, predict the topics for each article included in the test set.
Note that a research article can possibly have more than 1 topic. The research article abstracts and titles are sourced from the following 6 topics: