152 citations · 299 across the 35 of their papers we have counts for
35 papers
Experimental Analysis of Large-scale Learnable Vector Storage Compression
Hailin Zhang, Penghao Zhao, Xupeng Miao +4
Learnable embedding vector is one of the most important applications in machine learning, and is widely used in various database-related domains. However, the high dimensionality o…
ContTune: Continuous Tuning by Conservative Bayesian Optimization for Distributed Stream Data Processing Systems
Jinqing Lian, Xinyi Zhang, Yingxia Shao +4
The past decade has seen rapid growth of distributed stream data processing systems. Under these systems, a stream application is realized as a Directed Acyclic Graph (DAG) of oper…
Reinforcement Federated Learning Method Based on Adaptive OPTICS Clustering
Tianyu Zhao, Junping Du, Yingxia Shao +1
Federated learning is a distributed machine learning technology, which realizes the balance between data privacy protection and data sharing computing. To protect data privacy, fed…
RetroMAE-2: Duplex Masked Auto-Encoder For Pre-Training Retrieval-Oriented Language Models
Shitao Xiao, Zheng Liu, Yingxia Shao +1
To better support information retrieval tasks such as web search and open-domain question answering, growing effort is made to develop retrieval-oriented language models, e.g., Ret…
Efficient Graph Neural Network Inference at Large Scale
Xinyi Gao, Wentao Zhang, Yingxia Shao +3
Graph neural networks (GNNs) have demonstrated excellent performance in a wide range of applications. However, the enormous size of large-scale graphs hinders their applications un…
Distributed Graph Neural Network Training: A Survey
Yingxia Shao, Hongzheng Li, Xizhi Gu +6
Graph neural networks (GNNs) are a type of deep learning models that are trained on graphs and have been successfully applied in various domains. Despite the effectiveness of GNNs,…
Adaptive Dual Channel Convolution Hypergraph Representation Learning for Technological Intellectual Property
Yuxin Liu, Yawen Li, Yingxia Shao +1
In the age of big data, the demand for hidden information mining in technological intellectual property is increasing in discrete countries. Definitely, a considerable number of gr…
A Relational Triple Extraction Method Based on Feature Reasoning for Technological Patents
Runze Fang, Junping Du, Yingxia Shao +1
The relation triples extraction method based on table filling can address the issues of relation overlap and bias propagation. However, most of them only establish separate table f…
Diffusion Models: A Comprehensive Survey of Methods and Applications
Ling Yang, Zhilong Zhang, Yang Song +6
Diffusion models have emerged as a powerful new family of deep generative models with record-breaking performance in many applications, including image synthesis, video generation,…
A Rare Topic Discovery Model for Short Texts Based on Co-occurrence word Network
Chengjie Ma, Junping Du, Yingxia Shao +2
We provide a simple and general solution for the discovery of scarce topics in unbalanced short-text datasets, namely, a word co-occurrence network-based model CWIBTD, which can si…
Social Network Community Detection Based on Textual Content Similarity and Sentimental Tendency
Jie Gao, Junping Du, Yingxia Shao +2
Shared travel has gradually become one of the hot topics discussed on social networking platforms such as Micro Blog. In a timely manner, deeper network community detection on the…
A sentiment analysis model for car review texts based on adversarial training and whole word mask BERT
Xingchen Liu, Yawen Li, Yingxia Shao +2
In the field of car evaluation, more and more netizens choose to express their opinions on the Internet platform, and these comments will affect the decision-making of buyers and t…
Sentiment Analysis of Online Travel Reviews Based on Capsule Network and Sentiment Lexicon
Jia Wang, Junping Du, Yingxia Shao +1
With the development of online travel services, it has great application prospects to timely mine users' evaluation emotions for travel services and use them as indicators to guide…
RetroMAE: Pre-Training Retrieval-oriented Language Models Via Masked Auto-Encoder
Shitao Xiao, Zheng Liu, Yingxia Shao +1
Despite pre-training's progress in many important NLP tasks, it remains to explore effective pre-training strategies for dense retrieval. In this paper, we propose RetroMAE, a new…
Distill-VQ: Learning Retrieval Oriented Vector Quantization By Distilling Knowledge from Dense Embeddings
Shitao Xiao, Zheng Liu, Weihao Han +10
Vector quantization (VQ) based ANN indexes, such as Inverted File System (IVF) and Product Quantization (PQ), have been widely applied to embedding based document retrieval thanks…
Profiling and Evolution of Intellectual Property
Bowen Yu, Yingxia Shao, Ang Li
In recent years, with the rapid growth of Internet data, the number and types of scientific and technological resources are also rapidly expanding. However, the increase in the num…
Research on Intellectual Property Resource Profile and Evolution Law
Yuhui Wang, Yingxia Shao, Ang Li
In the era of big data, intellectual property-oriented scientific and technological resources show the trend of large data scale, high information density, and low value density, w…
Retrieval of Scientific and Technological Resources for Experts and Scholars
Suyu Ouyang, Yingxia Shao, Ang Li
Institutions of higher learning, research institutes and other scientific research units have abundant scientific and technological resources of experts and scholars, and these tal…
Scientific and Technological Text Knowledge Extraction Method of based on Word Mixing and GRU
Suyu Ouyang, Yingxia Shao, Junping Du +1
The knowledge extraction task is to extract triple relations (head entity-relation-tail entity) from unstructured text data. The existing knowledge extraction methods are divided i…
An I/O-Efficient Disk-based Graph System for Scalable Second-Order Random Walk of Large Graphs
Hongzheng Li, Yingxia Shao, Junping Du +2
Random walk is widely used in many graph analysis tasks, especially the first-order random walk. However, as a simplification of real-world problems, the first-order random walk is…
An Intellectual Property Entity Recognition Method Based on Transformer and Technological Word Information
Yuhui Wang, Junping Du, Yingxia Shao
Patent texts contain a large amount of entity information. Through named entity recognition, intellectual property entity information containing key information can be extracted fr…
Progressively Optimized Bi-Granular Document Representation for Scalable Embedding Based Retrieval
Shitao Xiao, Zheng Liu, Weihao Han +9
Ad-hoc search calls for the selection of appropriate answers from a massive-scale corpus. Nowadays, the embedding-based retrieval (EBR) becomes a promising solution, where deep lea…
Web Page Content Extraction Based on Multi-feature Fusion
Bowen Yu, Junping Du, Yingxia Shao
With the rapid development of Internet technology, people have more and more access to a variety of web page resources. At the same time, the current rapid development of deep lear…
Uni-Retriever: Towards Learning The Unified Embedding Based Retriever in Bing Sponsored Search
Jianjin Zhang, Zheng Liu, Weihao Han +9
Embedding based retrieval (EBR) is a fundamental building block in many web applications. However, EBR in sponsored search is distinguished from other generic scenarios and technic…