152 citations · 299 across the 35 of their papers we have counts for
11 papers · 1 filter
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…
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…
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…
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…
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…
Self-Supervised Graph Co-Training for Session-based Recommendation
Xin Xia, Hongzhi Yin, Junliang Yu +2
Session-based recommendation targets next-item prediction by exploiting user behaviors within a short time period. Compared with other recommendation paradigms, session-based recom…
Training Large-Scale News Recommenders with Pretrained Language Models in the Loop
Shitao Xiao, Zheng Liu, Yingxia Shao +2
News recommendation calls for deep insights of news articles' underlying semantics. Therefore, pretrained language models (PLMs), like BERT and RoBERTa, may substantially contribut…