64 Papers
235 Citations
Wei Xu is an academic researcher from Renmin University of China. The author has contributed to research in topics: Computer science & Big data. The author has an hindex of 18, co-authored 64 publications. Previous affiliations of Wei Xu include Chinese Academy of Sciences.
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Papers
Leveraging deep learning with LDA-based text analytics to detect automobile insurance fraud
Yibo Wang,Wei Xu +1 more
- 01 Jan 2018
TL;DR: A novel deep learning model for automobile insurance fraud detection that uses Latent Dirichlet Allocation (LDA)-based text analytics that outperforms widely used machine learning models, such as random forests and support vector machine.
315
HOBA: A novel feature engineering methodology for credit card fraud detection with a deep learning architecture
TL;DR: The main contribution of this work is the development of a fraud detection system that employs a deep learning architecture together with an advanced feature engineering process based on homogeneity-oriented behavior analysis (HOBA) to efficiently identify fraudulent transactions.
240
The determinants of crowdfunding success
Hui Yuan,Raymond Y. K. Lau,Wei Xu +2 more
- 01 Nov 2016
TL;DR: The design of a novel text analytics-based framework that can extract latent semantics from the textual descriptions of projects to predict the fund raising outcomes of these projects is designed and experimental results reveal that the proposed framework outperforms a classical LDA-based method in predicting fund raising success.
229
Parallel Aspect-Oriented Sentiment Analysis for Sales Forecasting with Big Data
TL;DR: The design and the large‐scale empirical test of a sentiment enhanced sales forecasting method that is empowered by a parallel co‐evolutionary extreme learning machine are presented, confirming that consumer sentiments mined from big data can improve the accuracy of sales forecasting across predictive models and datasets.
155
A Sentiment-Enhanced Hybrid Recommender System for Movie Recommendation: A Big Data Analytics Framework
Yibo Wang,Mingming Wang,Wei Xu +2 more
TL;DR: A movie recommendation framework based on a hybrid recommendation model and sentiment analysis on Spark platform is proposed to improve the accuracy and timeliness of mobile movie recommender system.