Intellectual
发表于 2025-3-26 22:40:08
Materials Integration Strategies,s, ranging from Computer Vision to Natural Language Processing. In this paper we focus on Facebook posts paired with “reactions” of multiple users, and we investigate their relationships with classes of emotions that are typically considered in the task of emotion detection. We are inspired by the i
perpetual
发表于 2025-3-27 03:22:11
https://doi.org/10.1007/978-3-030-30490-4artificial intelligence; classification; clustering; computational linguistics; computer networks; Human-
EXALT
发表于 2025-3-27 09:21:39
http://reply.papertrans.cn/17/1627/162646/162646_33.png
Foam-Cells
发表于 2025-3-27 09:35:33
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/162646.jpg
intangibility
发表于 2025-3-27 16:07:45
Artificial Neural Networks and Machine Learning – ICANN 2019: Text and Time Series978-3-030-30490-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
averse
发表于 2025-3-27 18:55:01
An Ensemble Model for Winning a Chinese Machine Reading Comprehension Competition a Chinese machine reading comprehension competition, namely the LES Cup Challenge, in October 2018. The competition introduces a big dataset of long articles and improperly labelled data, therefore challenges the state-of-the-art methods in this area. We proposed an ensemble model of four novel rec
运动的我
发表于 2025-3-28 00:01:46
http://reply.papertrans.cn/17/1627/162646/162646_37.png
受人支配
发表于 2025-3-28 04:37:48
Learning to Explain Chinese Slang Words has affected the accuracy of reading comprehension and word segmentation tasks. In this paper, we propose explaining Chinese slang word automatically for the first time. Unlike matching words in dictionary, we use a novel neural network called DCEAnn (a Dual Character-level Encoder using Attention-
昏迷状态
发表于 2025-3-28 07:54:57
http://reply.papertrans.cn/17/1627/162646/162646_39.png
Arroyo
发表于 2025-3-28 12:48:37
An Improved Method of Applying a Machine Translation Model to a Chinese Word Segmentation TaskHowever, directly applying the MT model to CWS task would introduce translation errors and result in poor word segmentation. In this paper, we propose a novel method named Translation Correcting to solve this problem. Based on the differences between CWS and MT, Translation Correcting eliminates tra