Search Results for author: Shaoping Ma

Found 18 papers, 10 papers with code

Towards Representation Alignment and Uniformity in Collaborative Filtering

1 code implementation26 Jun 2022 Chenyang Wang, Yuanqing Yu, Weizhi Ma, Min Zhang, Chong Chen, Yiqun Liu, Shaoping Ma

Then, we empirically analyze the learning dynamics of typical CF methods in terms of quantified alignment and uniformity, which shows that better alignment or uniformity both contribute to higher recommendation performance.

Collaborative Filtering Recommendation Systems

A Survey on the Fairness of Recommender Systems

no code implementations8 Jun 2022 Yifan Wang, Weizhi Ma, Min Zhang, Yiqun Liu, Shaoping Ma

First, we summarize fairness definitions in the recommendation and provide several views to classify fairness issues.

Fairness Recommendation Systems

Evaluating Interpolation and Extrapolation Performance of Neural Retrieval Models

1 code implementation25 Apr 2022 Jingtao Zhan, Xiaohui Xie, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma

For example, representation-based retrieval models perform almost as well as interaction-based retrieval models in terms of interpolation but not extrapolation.

A Survey on Dropout Methods and Experimental Verification in Recommendation

no code implementations5 Apr 2022 Yangkun Li, Weizhi Ma, Chong Chen, Min Zhang, Yiqun Liu, Shaoping Ma, Yuekui Yang

Among various methods of coping with overfitting, dropout is one of the representative ways.

Interpreting Dense Retrieval as Mixture of Topics

no code implementations27 Nov 2021 Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma

Dense Retrieval (DR) reaches state-of-the-art results in first-stage retrieval, but little is known about the mechanisms that contribute to its success.

Web Search via an Efficient and Effective Brain-Machine Interface

no code implementations14 Oct 2021 Xuesong Chen, Ziyi Ye, Xiaohui Xie, Yiqun Liu, Weihang Su, Shuqi Zhu, Min Zhang, Shaoping Ma

While search technologies have evolved to be robust and ubiquitous, the fundamental interaction paradigm has remained relatively stable for decades.

EEG

Learning Discrete Representations via Constrained Clustering for Effective and Efficient Dense Retrieval

4 code implementations12 Oct 2021 Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma

However, the efficiency of most existing DR models is limited by the large memory cost of storing dense vectors and the time-consuming nearest neighbor search (NNS) in vector space.

Information Retrieval Open-Domain Question Answering +1

Why Don't You Click: Neural Correlates of Non-Click Behaviors in Web Search

no code implementations22 Sep 2021 Ziyi Ye, Xiaohui Xie, Yiqun Liu, Zhihong Wang, Xuancheng Li, Jiaji Li, Xuesong Chen, Min Zhang, Shaoping Ma

Inspired by these findings, we conduct supervised learning tasks to estimate the usefulness of non-click results with brain signals and conventional information (i. e., content and context factors).

EEG

Jointly Optimizing Query Encoder and Product Quantization to Improve Retrieval Performance

5 code implementations2 Aug 2021 Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma

Compared with previous DR models that use brute-force search, JPQ almost matches the best retrieval performance with 30x compression on index size.

Information Retrieval Quantization

Optimizing Dense Retrieval Model Training with Hard Negatives

4 code implementations16 Apr 2021 Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma

ADORE replaces the widely-adopted static hard negative sampling method with a dynamic one to directly optimize the ranking performance.

Information Retrieval Representation Learning

THUIR@COLIEE-2020: Leveraging Semantic Understanding and Exact Matching for Legal Case Retrieval and Entailment

no code implementations24 Dec 2020 Yunqiu Shao, Bulou Liu, Jiaxin Mao, Yiqun Liu, Min Zhang, Shaoping Ma

We participated in the two case law tasks, i. e., the legal case retrieval task and the legal case entailment task.

Learning To Retrieve: How to Train a Dense Retrieval Model Effectively and Efficiently

2 code implementations20 Oct 2020 Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Min Zhang, Shaoping Ma

Through this process, it teaches the DR model how to retrieve relevant documents from the entire corpus instead of how to rerank a potentially biased sample of documents.

Passage Retrieval

RepBERT: Contextualized Text Embeddings for First-Stage Retrieval

3 code implementations28 Jun 2020 Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Min Zhang, Shaoping Ma

Although exact term match between queries and documents is the dominant method to perform first-stage retrieval, we propose a different approach, called RepBERT, to represent documents and queries with fixed-length contextualized embeddings.

Passage Ranking

Jointly Learning Explainable Rules for Recommendation with Knowledge Graph

1 code implementation9 Mar 2019 Weizhi Ma, Min Zhang, Yue Cao, Woojeong, Jin, Chenyang Wang, Yiqun Liu, Shaoping Ma, Xiang Ren

The framework encourages two modules to complement each other in generating effective and explainable recommendation: 1) inductive rules, mined from item-centric knowledge graphs, summarize common multi-hop relational patterns for inferring different item associations and provide human-readable explanation for model prediction; 2) recommendation module can be augmented by induced rules and thus have better generalization ability dealing with the cold-start issue.

Knowledge Graphs Recommendation Systems

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

no code implementations11 Feb 2015 Yongfeng Zhang, Min Zhang, Yiqun Liu, Shaoping Ma

In this paper, we focus on the problem of phrase-level sentiment polarity labelling and attempt to bridge the gap between phrase-level and review-level sentiment analysis.

Classification General Classification +1

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