vitamin-D
发表于 2025-3-21 20:01:41
书目名称Computational Linguistics and Intelligent Text Processing影响因子(影响力)<br> http://impactfactor.cn/2024/if/?ISSN=BK0232602<br><br> <br><br>书目名称Computational Linguistics and Intelligent Text Processing影响因子(影响力)学科排名<br> http://impactfactor.cn/2024/ifr/?ISSN=BK0232602<br><br> <br><br>书目名称Computational Linguistics and Intelligent Text Processing网络公开度<br> http://impactfactor.cn/2024/at/?ISSN=BK0232602<br><br> <br><br>书目名称Computational Linguistics and Intelligent Text Processing网络公开度学科排名<br> http://impactfactor.cn/2024/atr/?ISSN=BK0232602<br><br> <br><br>书目名称Computational Linguistics and Intelligent Text Processing被引频次<br> http://impactfactor.cn/2024/tc/?ISSN=BK0232602<br><br> <br><br>书目名称Computational Linguistics and Intelligent Text Processing被引频次学科排名<br> http://impactfactor.cn/2024/tcr/?ISSN=BK0232602<br><br> <br><br>书目名称Computational Linguistics and Intelligent Text Processing年度引用<br> http://impactfactor.cn/2024/ii/?ISSN=BK0232602<br><br> <br><br>书目名称Computational Linguistics and Intelligent Text Processing年度引用学科排名<br> http://impactfactor.cn/2024/iir/?ISSN=BK0232602<br><br> <br><br>书目名称Computational Linguistics and Intelligent Text Processing读者反馈<br> http://impactfactor.cn/2024/5y/?ISSN=BK0232602<br><br> <br><br>书目名称Computational Linguistics and Intelligent Text Processing读者反馈学科排名<br> http://impactfactor.cn/2024/5yr/?ISSN=BK0232602<br><br> <br><br>
净礼
发表于 2025-3-21 21:14:50
A Sentence Vector Based Over-Sampling Method for Imbalanced Emotion Classificationd training dataset. Evaluations on NLP&CC2013 Chinese micro blog emotion classification dataset shows that the obtained classifier achieves 48.4% average precision, an 11.9 percent improvement over the state-of-art performance on this dataset (at 36.5%). This result shows that the proposed over-samp
–scent
发表于 2025-3-22 00:54:00
http://reply.papertrans.cn/24/2327/232602/232602_3.png
Biguanides
发表于 2025-3-22 08:05:08
http://reply.papertrans.cn/24/2327/232602/232602_4.png
Intellectual
发表于 2025-3-22 09:51:50
http://reply.papertrans.cn/24/2327/232602/232602_5.png
努力赶上
发表于 2025-3-22 15:44:53
Extracting Social Events Based on Timeline and User Reliability Analysis on Twitterocial issues are selected and experimented on Korean twitter test set. The experimental results showed 97.2% in precision for the top 10 extracted events (P@10) on each day. This result shows that the proposed method is effective for extracting events in twitter corpus.
努力赶上
发表于 2025-3-22 18:45:55
Computational Linguistics and Intelligent Text Processing15th International C
ellagic-acid
发表于 2025-3-22 21:14:18
http://reply.papertrans.cn/24/2327/232602/232602_8.png
遗弃
发表于 2025-3-23 02:45:34
https://doi.org/10.1007/978-3-663-04930-2orrelation-based Feature-subset Selection. Considering overall performance on all emotion dimensions, our bimodal model outperforms the second best model of the challenge, and comes close to the best model. It also gives the best result when predicting Expectancy values.
被告
发表于 2025-3-23 05:44:27
,Modelluntersuchungen zur Strahllüftung,d training dataset. Evaluations on NLP&CC2013 Chinese micro blog emotion classification dataset shows that the obtained classifier achieves 48.4% average precision, an 11.9 percent improvement over the state-of-art performance on this dataset (at 36.5%). This result shows that the proposed over-samp