Search Results for author: Zhumin Chen

Found 29 papers, 20 papers with code

Membership Inference Attacks Against Recommender Systems

1 code implementation16 Sep 2021 Minxing Zhang, Zhaochun Ren, Zihan Wang, Pengjie Ren, Zhumin Chen, Pengfei Hu, Yang Zhang

In this paper, we make the first attempt on quantifying the privacy leakage of recommender systems through the lens of membership inference.

Recommendation Systems

M^2-MedDialog: A Dataset and Benchmarks for Multi-domain Multi-service Medical Dialogues

1 code implementation1 Sep 2021 Guojun Yan, Jiahuan Pei, Pengjie Ren, Zhumin Chen, Zhaochun Ren, Huasheng Liang

In this work, we first build a Multiple-domain Multiple-service medical dialogue (M^2-MedDialog)dataset, which contains 1, 557 conversations between doctors and patients, covering 276 types of diseases, 2, 468 medical entities, and 3 specialties of medical services.

Language Modelling

Learning to Ask Conversational Questions by Optimizing Levenshtein Distance

1 code implementation ACL 2021 Zhongkun Liu, Pengjie Ren, Zhumin Chen, Zhaochun Ren, Maarten de Rijke, Ming Zhou

Conversational Question Simplification (CQS) aims to simplify self-contained questions into conversational ones by incorporating some conversational characteristics, e. g., anaphora and ellipsis.

Few-Shot Electronic Health Record Coding through Graph Contrastive Learning

1 code implementation29 Jun 2021 Shanshan Wang, Pengjie Ren, Zhumin Chen, Zhaochun Ren, Huasheng Liang, Qiang Yan, Evangelos Kanoulas, Maarten de Rijke

We seek to improve the performance for both frequent and rare ICD codes by using a contrastive graph-based EHR coding framework, CoGraph, which re-casts EHR coding as a few-shot learning task.

Contrastive Learning Few-Shot Learning

Improving Transformer-based Sequential Recommenders through Preference Editing

no code implementations23 Jun 2021 Muyang Ma, Pengjie Ren, Zhumin Chen, Zhaochun Ren, Huasheng Liang, Jun Ma, Maarten de Rijke

By doing so, the SR model is able to learn how to identify common and unique user preferences, and thereby do better user preference extraction and representation.

Self-Supervised Learning Sequential Recommendation

Wizard of Search Engine: Access to Information Through Conversations with Search Engines

1 code implementation18 May 2021 Pengjie Ren, Zhongkun Liu, Xiaomeng Song, Hongtao Tian, Zhumin Chen, Zhaochun Ren, Maarten de Rijke

(2) We release a benchmark dataset, called wizard of search engine (WISE), which allows for comprehensive and in-depth research on all aspects of CIS.

Information Seeking Intent Detection +1

DCAP: Deep Cross Attentional Product Network for User Response Prediction

1 code implementation18 May 2021 Zekai Chen, Fangtian Zhong, Zhumin Chen, Xiao Zhang, Robert Pless, Xiuzhen Cheng

Prior studies in predicting user response leveraged the feature interactions by enhancing feature vectors with products of features to model second-order or high-order cross features, either explicitly or implicitly.

Recommendation Systems

Abstractive Opinion Tagging

1 code implementation18 Jan 2021 Qintong Li, Piji Li, Xinyi Li, Zhaochun Ren, Zhumin Chen, Maarten de Rijke

In this paper, we propose the abstractive opinion tagging task, where systems have to automatically generate a ranked list of opinion tags that are based on, but need not occur in, a given set of user-generated reviews.

EmpDG: Multi-resolution Interactive Empathetic Dialogue Generation

1 code implementation COLING 2020 Qintong Li, Hongshen Chen, Zhaochun Ren, Pengjie Ren, Zhaopeng Tu, Zhumin Chen

In response to this problem, we propose a multi-resolution adversarial model {--} EmpDG, to generate more empathetic responses.

Dialogue Generation

Mixed Information Flow for Cross-domain Sequential Recommendations

1 code implementation1 Dec 2020 Muyang Ma, Pengjie Ren, Zhumin Chen, Zhaochun Ren, Lifan Zhao, Jun Ma, Maarten de Rijke

One of the key challenges in cross-domain sequential recommendation is to grasp and transfer the flow of information from multiple domains so as to promote recommendations in all domains.

Sequential Recommendation Transfer Learning

Knowledge Bridging for Empathetic Dialogue Generation

1 code implementation21 Sep 2020 Qintong Li, Piji Li, Zhaochun Ren, Pengjie Ren, Zhumin Chen

Finally, to generate the empathetic response, we propose an emotional cross-attention mechanism to learn the emotional dependencies from the emotional context graph.

Dialogue Generation

Conversations with Search Engines: SERP-based Conversational Response Generation

1 code implementation29 Apr 2020 Pengjie Ren, Zhumin Chen, Zhaochun Ren, Evangelos Kanoulas, Christof Monz, Maarten de Rijke

In this paper, we address the problem of answering complex information needs by conversing conversations with search engines, in the sense that users can express their queries in natural language, and directly receivethe information they need from a short system response in a conversational manner.

Conversational Response Generation Conversational Search

A Neural Topical Expansion Framework for Unstructured Persona-oriented Dialogue Generation

2 code implementations6 Feb 2020 Minghong Xu, Piji Li, Haoran Yang, Pengjie Ren, Zhaochun Ren, Zhumin Chen, Jun Ma

To address this, we propose a neural topical expansion framework, namely Persona Exploration and Exploitation (PEE), which is able to extend the predefined user persona description with semantically correlated content before utilizing them to generate dialogue responses.

Dialogue Generation

EmpDG: Multiresolution Interactive Empathetic Dialogue Generation

1 code implementation20 Nov 2019 Qintong Li, Hongshen Chen, Zhaochun Ren, Pengjie Ren, Zhaopeng Tu, Zhumin Chen

In response to this problem, we propose a multi-resolution adversarial model -- EmpDG, to generate more empathetic responses.

Dialogue Generation

Parallel Split-Join Networks for Shared-account Cross-domain Sequential Recommendations

no code implementations6 Oct 2019 Wenchao Sun, Muyang Ma, Pengjie Ren, Yujie Lin, Zhumin Chen, Zhaochun Ren, Jun Ma, Maarten de Rijke

We study sequential recommendation in a particularly challenging context, in which multiple individual users share asingle account (i. e., they have a shared account) and in which user behavior is available in multiple domains (i. e., recommendations are cross-domain).

Sequential Recommendation

Thinking Globally, Acting Locally: Distantly Supervised Global-to-Local Knowledge Selection for Background Based Conversation

1 code implementation26 Aug 2019 Pengjie Ren, Zhumin Chen, Christof Monz, Jun Ma, Maarten de Rijke

Given a conversational context and background knowledge, we first learn a topic transition vector to encode the most likely text fragments to be used in the next response, which is then used to guide the local KS at each decoding timestamp.

Improving Outfit Recommendation with Co-supervision of Fashion Generation

no code implementations24 Aug 2019 Yujie Lin, Pengjie Ren, Zhumin Chen, Zhaochun Ren, Jun Ma, Maarten de Rijke

FARM improves visual understanding by incorporating the supervision of generation loss, which we hypothesize to be able to better encode aesthetic information.

RefNet: A Reference-aware Network for Background Based Conversation

1 code implementation18 Aug 2019 Chuan Meng, Pengjie Ren, Zhumin Chen, Christof Monz, Jun Ma, Maarten de Rijke

In this paper, we propose a Reference-aware Network (RefNet) to address the two issues.

RepeatNet: A Repeat Aware Neural Recommendation Machine for Session-based Recommendation

1 code implementation6 Dec 2018 Pengjie Ren, Zhumin Chen, Jing Li, Zhaochun Ren, Jun Ma, Maarten de Rijke

RepeatNet integrates a regular neural recommendation approach in the decoder with a new repeat recommendation mechanism that can choose items from a user's history and recommends them at the right time.

Session-Based Recommendations

Neural Attentive Session-based Recommendation

3 code implementations13 Nov 2017 Jing Li, Pengjie Ren, Zhumin Chen, Zhaochun Ren, Jun Ma

Specifically, we explore a hybrid encoder with an attention mechanism to model the user's sequential behavior and capture the user's main purpose in the current session, which are combined as a unified session representation later.

Session-Based Recommendations

Neural Att entive Session-based Recommendation

1 code implementation CIKM 2017 Jing Li, Pengjie Ren, Zhumin Chen, Zhaochun Ren, Tao Lian, Jun Ma

Specifically, we explore a hybrid encoder with an attention mechanism to model the user’s sequential behavior and capture the user’s main purpose in the current session, which are combined as a unified session representation later.

Session-Based Recommendations

A Redundancy-Aware Sentence Regression Framework for Extractive Summarization

no code implementations COLING 2016 Pengjie Ren, Furu Wei, Zhumin Chen, Jun Ma, Ming Zhou

Existing sentence regression methods for extractive summarization usually model sentence importance and redundancy in two separate processes.

Document Summarization Extractive Summarization +1

Cannot find the paper you are looking for? You can Submit a new open access paper.