Titlebook: Cognitive Computing – ICCC 2022; 6th International Co Yujiu Yang,Xiaohui Wang,Liang-Jie Zhang Conference proceedings 2022 The Editor(s) (if

船員

莊嚴(yán)

978-3-031-23584-9The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

滔滔不絕的人

semble

Jean-Numa Ducange,Elisa Marcobellirvice dialogue data, which effectively improves the matching accuracy of the framework. We conduct extensive experiments on CHUZHOU and EIP customer service questioning datasets from KONKA. The result shows that CFTM outperforms baselines across all metrics, achieving a 2.5 improvement in F1-Score a

別炫耀

https://doi.org/10.1007/978-94-009-8040-2ing in business systems. By observing the characteristics of mapping data in business systems, we firstly use FastText to learn word representation containing semantic information, and then adopt the LSTM model to extract features for text classification automatically. Experimental results show that

Lobotomy

樂(lè)器演奏者

分期付款

Automated Data Mapping Based on FastText and LSTM for Business Systemsing in business systems. By observing the characteristics of mapping data in business systems, we firstly use FastText to learn word representation containing semantic information, and then adopt the LSTM model to extract features for text classification automatically. Experimental results show that

混合,攙雜

巨頭

Solving a?Cloze Test for?Generative Commonsense Question Answerings are tackling the answer generation of commonsense questions, which is more difficult than multiple-choice. This motivates us to delve into the answer generation ability of pre-trained language models (PLMs). Other than utilizing knowledge bases to extract commonsense-related knowledge to answer co