• Publications
  • Influence
Chinese Open Relation Extraction and Knowledge Base Establishment
TLDR
This article proposes a novel unsupervised linguistics-based Chinese ORE model based on Dependency Semantic Normal Forms (DSNFs), which can automatically discover arbitrary relations without any manually labeled datasets, and establishes a large-scale corpus of entity and relation. Expand
Chinese Named Entity Recognition with Character-Word Mixed Embedding
TLDR
This work proposes a Chinese NER method based on Character-Word Mixed Embedding (CWME), and the method is in accord with the pipeline of Chinese natural language processing and shows that incorporating CWME can effectively improve the performance for the Chinese corpus with state-of-the-art neural architectures widely used in NER. Expand
Bert with Dynamic Masked Softmax and Pseudo Labeling for Hierarchical Product Classification
TLDR
A BERT-based ensemble model is proposed to address the HPC challenge in SWC2020MWPD Task 2.0 with a masked matrix for each category level based on the hierarchical category structure, which can dynamically filter out the child categories unrelated to the current parent category and eliminate the negative effect of category inconsistency. Expand
Pairwise learning to recommend with both users' and items' contextual information
TLDR
The authors integrate both users’ and items’ social contextual information into a pairwise learning to recommendation model (named as UIContextRank) to enhance ranking accuracy and recommendation quality and extend UIC ontextRank in a distributed environment to improve efficiency and scalability. Expand
Aspect-based Financial Sentiment Analysis with Deep Neural Networks
TLDR
A neural network model is proposed, Attention-based LSTM model with the Aspect information (ALA), to solve the financial opinion mining problem introduced by the WWW 2018 shared task. Expand
Study on the Chinese Word Semantic Relation Classification with Word Embedding
TLDR
The proposed method to the NLPCC 2017 shared task on Chinese word semantic relation classification won second place and can achieve competitive results with small training corpus. Expand
Triple Trustworthiness Measurement for Knowledge Graph
TLDR
A knowledge graph triple trustworthiness measurement model that quantify their semantic correctness and the true degree of the facts expressed and achieved significant and consistent improvements compared with other models. Expand
PRACE: A Taxi Recommender for Finding Passengers with Deep Learning Approaches
TLDR
A real-time recommender system for taxi drivers to find a next passenger and start a new trip efficiently, based on historical GPS trajectories of taxis, using deep neural networks and the map meshing method. Expand
Enhanced attentive convolutional neural networks for sentence pair modeling
TLDR
This paper proposes Enhanced Attentive Convolutional Neural Networks (EACNNs) for modeling sentence pairs to make full use of the characteristics of convolution, and exploits two attention schemes: attention before representation and attention after representation to capture the interaction information of sentence pairs. Expand
TTMF: A Triple Trustworthiness Measurement Frame for Knowledge Graphs
TLDR
A unified knowledge graph triple trustworthiness measurement framework to calculate the confidence values for the triples that quantify its semantic correctness and the true degree of the facts expressed is established. Expand
...
1
2
3
...