| Issue |
MATEC Web Conf.
Volume 232, 2018
2018 2nd International Conference on Electronic Information Technology and Computer Engineering (EITCE 2018)
|
|
|---|---|---|
| Article Number | 01022 | |
| Number of page(s) | 5 | |
| Section | Network Security System, Neural Network and Data Information | |
| DOI | https://doi.org/10.1051/matecconf/201823201022 | |
| Published online | 19 November 2018 | |
A study on the subject classification of the NBA match reports
1
Beijing Key Laboratory of Internet Culture and Digital Dissemination Research, Beijing Information Science and Technology University, Beijing, China
2
Beijing Key Laboratory of Internet Culture and Digital Dissemination Research, Beijing Information Science and Technology University, Beijing, China
3
Beijing Key Laboratory of Internet Culture and Digital Dissemination Research, Beijing Information Science and Technology University, Beijing, China
4
Beijing Key Laboratory of Internet Culture and Digital Dissemination Research, Beijing Information Science and Technology University, Beijing, China
* Corresponding author: a Zhe Wang:525322746@qq.com
In this paper, we study the task of template building in automatically generate NBA match reports from NBA live text. As a preliminary study, we collect and process the historical reports compiled by the editors and get different kinds of sentences. Our innovative proposal is to divide the NBA match reports into 11 categories, which covering almost all cases. We use different machine learning methods to classify sentences. Each class finally constructs a template library to service the next automatic writing. By comparing different methods, we get a higher accuracy classification structure. The evaluation results show that our method does construct a template library.
© The Authors, published by EDP Sciences, 2018
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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