Yongfeng Zhang

research

∙ 08/21/2020

COOKIE: A Dataset for Conversational Recommendation over Knowledge Graphs in E-commerce

In this work, we present a new dataset for conversational recommendation...

33 Zuohui Fu, et al. ∙

research

∙ 08/20/2020

Neural Logic Reasoning

Recent years have witnessed the success of deep neural networks in many ...

31 Shaoyun Shi, et al. ∙

research

∙ 08/19/2020

E-commerce Recommendation with Weighted Expected Utility

Different from shopping at retail stores, consumers on e-commerce platfo...

0 Zhichao Xu, et al. ∙

research

∙ 07/26/2020

Neural-Symbolic Reasoning over Knowledge Graph for Multi-stage Explainable Recommendation

Recent work on recommender systems has considered external knowledge gra...

0 Yikun Xian, et al. ∙

research

∙ 07/06/2020

Learning Personalized Risk Preferences for Recommendation

The rapid growth of e-commerce has made people accustomed to shopping on...

0 Yingqiang Ge, et al. ∙

research

∙ 07/06/2020

Understanding Echo Chambers in E-commerce Recommender Systems

Personalized recommendation benefits users in accessing contents of inte...

0 Yingqiang Ge, et al. ∙

research

∙ 06/30/2020

Learning Post-Hoc Causal Explanations for Recommendation

State-of-the-art recommender systems have the ability to generate high-q...

0 Shuyuan Xu, et al. ∙

research

∙ 06/03/2020

Fairness-Aware Explainable Recommendation over Knowledge Graphs

There has been growing attention on fairness considerations recently, es...

1 Zuohui Fu, et al. ∙

research

∙ 05/16/2020

Neural Collaborative Reasoning

Collaborative Filtering (CF) has been an important approach to recommend...

0 Hanxiong Chen, et al. ∙

research

∙ 02/03/2020

IART: Intent-aware Response Ranking with Transformers in Information-seeking Conversation Systems

Personal assistant systems, such as Apple Siri, Google Assistant, Amazon...

0 Liu Yang, et al. ∙

research

∙ 10/17/2019

Neural Logic Networks

Recent years have witnessed the great success of deep neural networks in...

0 Shaoyun Shi, et al. ∙

research

∙ 10/16/2019

Similarity Driven Approximation for Text Analytics

Text analytics has become an important part of business intelligence as ...

0 Guangyan Hu, et al. ∙

research

∙ 09/16/2019

Explainable Product Search with a Dynamic Relation Embedding Model

Product search is one of the most popular methods for customers to disco...

0 Qingyao Ai, et al. ∙

research

∙ 09/04/2019

Conversational Product Search Based on Negative Feedback

Intelligent assistants change the way people interact with computers and...

0 Keping Bi, et al. ∙

research

∙ 08/26/2019

Attentive History Selection for Conversational Question Answering

Conversational question answering (ConvQA) is a simplified but concrete ...

0 Chen Qu, et al. ∙

research

∙ 06/12/2019

Reinforcement Knowledge Graph Reasoning for Explainable Recommendation

Recent advances in personalized recommendation have sparked great intere...

0 Yikun Xian, et al. ∙

research

∙ 05/14/2019

BERT with History Answer Embedding for Conversational Question Answering

Conversational search is an emerging topic in the information retrieval ...

0 Chen Qu, et al. ∙

research

∙ 04/29/2019

Relational Collaborative Filtering:Modeling Multiple Item Relations for Recommendation

Existing item-based collaborative filtering (ICF) methods leverage only ...

0 Xin Xin, et al. ∙

research

∙ 04/15/2019

Personalized Context-aware Re-ranking for E-commerce Recommender Systems

Ranking is a core task in E-commerce recommender systems, which aims at ...

0 Changhua Pei, et al. ∙

research

∙ 02/03/2019

Value-aware Recommendation based on Reinforced Profit Maximization in E-commerce Systems

Existing recommendation algorithms mostly focus on optimizing traditiona...

0 Changhua Pei, et al. ∙

research

∙ 01/11/2019

Answer Interaction in Non-factoid Question Answering Systems

Information retrieval systems are evolving from document retrieval to an...

0 Chen Qu, et al. ∙

research

∙ 01/11/2019

User Intent Prediction in Information-seeking Conversations

Conversational assistants are being progressively adopted by the general...

0 Chen Qu, et al. ∙

research

∙ 11/11/2018

Attentive Aspect Modeling for Review-aware Recommendation

In recent years, many studies extract aspects from user reviews and inte...

0 Xinyu Guan, et al. ∙

research

∙ 05/09/2018

Learning Heterogeneous Knowledge Base Embeddings for Explainable Recommendation

Providing model-generated explanations in recommender systems is importa...

0 Qingyao Ai, et al. ∙

research

∙ 05/01/2018

Response Ranking with Deep Matching Networks and External Knowledge in Information-seeking Conversation Systems

Intelligent personal assistant systems with either text-based or voice-b...

0 Liu Yang, et al. ∙

research

∙ 04/30/2018

Explainable Recommendation: A Survey and New Perspectives

Explainable Recommendation refers to the personalized recommendation alg...

0 Yongfeng Zhang, et al. ∙

research

∙ 04/23/2018

Analyzing and Characterizing User Intent in Information-seeking Conversations

Understanding and characterizing how people interact in information-seek...

0 Chen Qu, et al. ∙

research

∙ 03/17/2018

Learning over Knowledge-Base Embeddings for Recommendation

State-of-the-art recommendation algorithms -- especially the collaborati...

0 Yongfeng Zhang, et al. ∙

research

∙ 01/31/2018

Visually Explainable Recommendation

Images account for a significant part of user decisions in many applicat...

0 Xu Chen, et al. ∙

research

∙ 08/21/2017

Explainable Recommendation: Theory and Applications

Although personalized recommendation has been investigated for decades, ...

0 Yongfeng Zhang, et al. ∙

research

∙ 02/11/2015

Boost Phrase-level Polarity Labelling with Review-level Sentiment Classification

Sentiment analysis on user reviews helps to keep track of user reactions...

0 Yongfeng Zhang, et al. ∙

Yongfeng Zhang

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