Zhiqiang Zhang

Distributed Deep Forest and its Application to Automatic Detection of Cash-out Fraud

2018 · arXiv (Cornell University)

Internet companies are facing the need for handling large-scale machine learning applications on a daily basis and distributed implementation of machine learning algorithms which can handle extra-large scale tasks with great performance is widely needed. …

Graph Representation Learning for Merchant Incentive Optimization in Mobile Payment Marketing

2019

Mobile payment such as Alipay has been widely used in our daily lives. To further promote the mobile payment activities, it is important to run marketing campaigns under a limited budget by providing incentives such …

Graph Representation Learning for Merchant Incentive Optimization in Mobile Payment Marketing

2020 · arXiv (Cornell University)

Mobile payment such as Alipay has been widely used in our daily lives. To further promote the mobile payment activities, it is important to run marketing campaigns under a limited budget by providing incentives such …

Counterfactual Review-based Recommendation

2021

Incorporating review information into the recommender system has been demonstrated to be an effective method for boosting the recommendation performance. Previous research mainly focus on designing advanced architectures to better profile the users and items. …

Can Small Language Models be Good Reasoners for Sequential Recommendation?

2024 · arXiv (Cornell University)

Large language models (LLMs) open up new horizons for sequential recommendations, owing to their remarkable language comprehension and generation capabilities. However, there are still numerous challenges that should be addressed to successfully implement sequential recommendations …

Similarity is Not All You Need: Endowing Retrieval Augmented Generation with Multi Layered Thoughts

2024 · arXiv (Cornell University)

In recent years, large language models (LLMs) have made remarkable achievements in various domains. However, the untimeliness and cost of knowledge updates coupled with hallucination issues of LLMs have curtailed their applications in knowledge intensive …

Have We Designed Generalizable Structural Knowledge Promptings? Systematic Evaluation and Rethinking

2024 · arXiv (Cornell University)

Large language models (LLMs) have demonstrated exceptional performance in text generation within current NLP research. However, the lack of factual accuracy is still a dark cloud hanging over the LLM skyscraper. Structural knowledge prompting (SKP) …

Semantic Path based Personalized Recommendation on Weighted Heterogeneous Information Networks

2015

Recently heterogeneous information network (HIN) analysis has attracted a lot of attention, and many data mining tasks have been exploited on HIN. As an important data mining task, recommender system includes a lot of object …