Search Results - "Su, Jindian"

Improving BERT-Based Text Classification With Auxiliary Sentence and Domain Knowledge by Yu, Shanshan, Su, Jindian, Luo, Da

“…General language model BERT pre-trained on cross-domain text corpus, BookCorpus and Wikipedia, achieves excellent performance on a couple of natural language…”
Get full text

Enhancing Aspect-Based Sentiment Analysis With Capsule Network by Su, Jindian, Yu, Shanshan, Luo, Da

“…Existing feature-based neural approaches for aspect-based sentiment analysis (ABSA) try to improve their performance with pre-trained word embeddings and by…”
Get full text

Multi-Turn Response Selection for Chatbots With Hierarchical Aggregation Network of Multi-Representation by Mao, Guanwen, Su, Jindian, Yu, Shanshan, Luo, Da

“…Matching an appropriate response with its multi-turn context is a crucial challenge in retrieval-based chatbots. Current studies construct multiple…”
Get full text

Improving Distantly Supervised Relation Classification With Attention and Semantic Weight by Zhu, Zhangdong, Su, Jindian, Zhou, Yang

“…Distantly supervised relation classification aims at identifying the relationship between two given entities and plays an essential part in natural language…”
Get full text

An Effective Way To Reduce Network Transmission In Backup System by Chao, Yun, Su, JinDian

“…Content-defined chunking (CDC) algorithms play an important role in data deduplication, data synchronization and cloud storage. The existing CDC algorithms…”
Get full text

Bidirectional Inference Model with Multiple Latent Variables Based on Variational Auto-encoders by Zhao, Yanbin, Su, Jindian

“…One of the key tasks of open-domain dialog system is to generate diverse and coherent dialog responses.However, one-way inference from above information alone…”
Get full text

A Category Theoretic Method of Temporal Data Model by Decheng Miao, Jianqing Xi, Jindian Su

“…Temporal data model is the mainline of trends in temporal database technology, and it is the core and basis of temporal database system development. Existing…”
Get full text

Unified Named Entity Recognition as Multi-Label Sequence Generation by Su, Jindian, Yu, Hong

“…Currently, named entity recognition (NER) task can be mainly divided into three types: flat, nested, and discontinuous. In previous work, different types of…”
Get full text

UCSC-CGEC: A Unified Approach For Chinese Spelling Check And Grammatical Error Correction by Su, Jindian, Xie, Yunhao, Mou, Yueqi

“…Chinese Spelling Check (CSC) and Chinese Grammatical Error Correction (CGEC) are two important and challenging tasks in the Natural Language Processing (NLP)…”
Get full text

Robust Adaptive Feature Enhancement and Contrastive Clustering for New Intent Discovery by Chen, Keyue, Su, Jindian, Pan, Zijian

“…The primary goal of the New Intent Discovery (NID) algorithm is to discover specific intentions from user queries. State-of-the-art approaches currently focus…”
Get full text

A BERT-based Approach with Relation-aware Attention for Knowledge Base Question Answering by Luo, Da, Su, Jindian, Yu, Shanshan

“…Knowledge Base Question Answering (KBQA), which uses the facts in the knowledge base (KB) to answer natural language questions, has received extensive…”
Get full text

A coloured Petri net model for composite behaviors in multi-agent system by Su Jindian, Guo Heqing, Yu Shanshan

“…Traditional informal description methods have obvious shortcomings in describing complex composite behaviors in MAS, not only due to their hierarchical and…”
Get full text

CCCSpell: A Consistent and Contrastive Learning Approach with Character Similarity for Chinese Spelling Check by Su, Jindian, Lin, Xiaobin, Xie, Yunhao, Cheng, Zehua

“…Chinese Spelling Check (CSC) is a task to detect and correct Chinese misspellings. Existing methods have adopted pre-trained language models (PLMs) and…”
Get full text

Multi-Turn Response Selection for Chatbots With Hierarchical Aggregation Network of Multi-Representation by Mao, Guanwen, Su, Jindian, Yu, Shanshan, Luo, Da

“…Matching an appropriate response with its multi-turn context is a crucial challenge in retrieval-based chatbots. Current studies construct multiple…”
Get full text

Final Semantics of Object Behavioral Equivalence by Yu, Shanshan, Li, Shixian, Su, Jindian

“…Behavioral equivalence is an important issue in the researches of dynamic substitutability for objects and it is still difficult to verify it effectively and…”
Get full text