Search Results for author: Chenrui Zhang

Found 8 papers, 1 papers with code

Deep learning based Chinese text sentiment mining and stock market correlation research

no code implementations10 May 2022 Chenrui Zhang

We explore how to crawl financial forum data such as stock bars and combine them with deep learning models for sentiment analysis.

Sentiment Analysis

Research on the correlation between text emotion mining and stock market based on deep learning

no code implementations9 May 2022 Chenrui Zhang

This paper discusses how to crawl the data of financial forums such as stock bar, and conduct emotional analysis combined with the in-depth learning model.

ST-PIL: Spatial-Temporal Periodic Interest Learning for Next Point-of-Interest Recommendation

no code implementations6 Apr 2021 Qiang Cui, Chenrui Zhang, Yafeng Zhang, Jinpeng Wang, Mingchen Cai

Specifically, in the long-term module, we learn the temporal periodic interest of daily granularity, then utilize intra-level attention to form long-term interest.

Optimizing Multiple Performance Metrics with Deep GSP Auctions for E-commerce Advertising

no code implementations5 Dec 2020 Zhilin Zhang, Xiangyu Liu, Zhenzhe Zheng, Chenrui Zhang, Miao Xu, Junwei Pan, Chuan Yu, Fan Wu, Jian Xu, Kun Gai

In e-commerce advertising, the ad platform usually relies on auction mechanisms to optimize different performance metrics, such as user experience, advertiser utility, and platform revenue.

TGG: Transferable Graph Generation for Zero-shot and Few-shot Learning

1 code implementation30 Aug 2019 Chenrui Zhang, Xiaoqing Lyu, Zhi Tang

A dual relation propagation approach is proposed, where relations captured by the generated graph are separately propagated from the seen and unseen subgraphs.

Few-Shot Learning Graph Attention +2

Visual Data Synthesis via GAN for Zero-Shot Video Classification

no code implementations26 Apr 2018 Chenrui Zhang, Yuxin Peng

First, we propose multi-level semantic inference to boost video feature synthesis, which captures the discriminative information implied in joint visual-semantic distribution via feature-level and label-level semantic inference.

Classification General Classification +2

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