Overview of the NLPCC 2017 Shared Task: Chinese News Headline Categorization
Xipeng Qiu, Jingjing Gong, Xuanjing Huang
TL;DR
This paper provides an overview of the NLPCC 2017 shared task focused on categorizing Chinese news headlines into 18 classes, including details about the dataset and resources for participants.
Contribution
It introduces a new dataset of Chinese news headlines with labels and shares resources for future research in headline classification.
Findings
Dataset contains 12,000 labeled headlines.
Accessible code and dataset for research use.
Framework established for headline categorization tasks.
Abstract
In this paper, we give an overview for the shared task at the CCF Conference on Natural Language Processing \& Chinese Computing (NLPCC 2017): Chinese News Headline Categorization. The dataset of this shared task consists 18 classes, 12,000 short texts along with corresponded labels for each class. The dataset and example code can be accessed at https://github.com/FudanNLP/nlpcc2017_news_headline_categorization.
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Taxonomy
TopicsTopic Modeling · Text and Document Classification Technologies · Natural Language Processing Techniques