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08/29/2023
Knowledge-based Multiple Adaptive Spaces Fusion for Recommendation
Since Knowledge Graphs (KGs) contain rich semantic information, recently...
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08/10/2023
Adaptive Taxonomy Learning and Historical Patterns Modelling for Patent Classification
Patent classification aims to assign multiple International Patent Class...
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07/31/2023
Scaling Sentence Embeddings with Large Language Models
Large language models (LLMs) have recently garnered significant interest...
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05/27/2023
Modeling Dynamic Heterogeneous Graph and Node Importance for Future Citation Prediction
Accurate citation count prediction of newly published papers could help ...
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05/18/2023
Seq-HGNN: Learning Sequential Node Representation on Heterogeneous Graph
Recent years have witnessed the rapid development of heterogeneous graph...
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05/06/2023
Attacking Pre-trained Recommendation
Recently, a series of pioneer studies have shown the potency of pre-trai...
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04/28/2023
Ensemble Modeling with Contrastive Knowledge Distillation for Sequential Recommendation
Sequential recommendation aims to capture users' dynamic interest and pr...
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04/18/2023
Frequency Enhanced Hybrid Attention Network for Sequential Recommendation
The self-attention mechanism, which equips with a strong capability of m...
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04/16/2023
Meta-optimized Contrastive Learning for Sequential Recommendation
Contrastive Learning (CL) performances as a rising approach to address t...
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03/21/2023
A Survey on Causal Inference for Recommendation
Recently, causal inference has attracted increasing attention from resea...
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11/20/2022
RHCO: A Relation-aware Heterogeneous Graph Neural Network with Contrastive Learning for Large-scale Graphs
Heterogeneous graph neural networks (HGNNs) have been widely applied in ...
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11/19/2022
Exploring the Confounding Factors of Academic Career Success: An Empirical Study with Deep Predictive Modeling
Understanding determinants of success in academic careers is critically ...
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10/12/2022
Pruning Pre-trained Language Models Without Fine-Tuning
To overcome the overparameterized problem in Pre-trained Language Models...
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08/24/2022
A Hierarchical Interactive Network for Joint Span-based Aspect-Sentiment Analysis
Recently, some span-based methods have achieved encouraging performances...
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06/30/2022
Customized Conversational Recommender Systems
Conversational recommender systems (CRS) aim to capture user's current i...
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06/26/2022
Memory-Guided Multi-View Multi-Domain Fake News Detection
The wide spread of fake news is increasingly threatening both individual...
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05/29/2022
TAR: Neural Logical Reasoning across TBox and ABox
Many ontologies, i.e., Description Logic (DL) knowledge bases, have been...
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05/19/2022
Detect Professional Malicious User with Metric Learning in Recommender Systems
In e-commerce, online retailers are usually suffering from professional ...
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05/19/2022
Personalized Prompts for Sequential Recommendation
Pre-training models have shown their power in sequential recommendation....
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05/10/2022
Selective Fairness in Recommendation via Prompts
Recommendation fairness has attracted great attention recently. In real-...
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05/05/2022
Exploiting Global and Local Hierarchies for Hierarchical Text Classification
Hierarchical text classification aims to leverage label hierarchy in mul...
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05/02/2022
Positive-Unlabeled Learning with Adversarial Data Augmentation for Knowledge Graph Completion
Most real-world knowledge graphs (KG) are far from complete and comprehe...
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04/20/2022
Generalizing to the Future: Mitigating Entity Bias in Fake News Detection
The wide dissemination of fake news is increasingly threatening both ind...
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04/20/2022
User-Centric Conversational Recommendation with Multi-Aspect User Modeling
Conversational recommender systems (CRS) aim to provide highquality reco...
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03/20/2022
Multi-view Multi-behavior Contrastive Learning in Recommendation
Multi-behavior recommendation (MBR) aims to jointly consider multiple be...
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01/12/2022
PromptBERT: Improving BERT Sentence Embeddings with Prompts
The poor performance of the original BERT for sentence semantic similari...
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01/11/2022
Stock Movement Prediction Based on Bi-typed and Hybrid-relational Market Knowledge Graph via Dual Attention Networks
Stock Movement Prediction (SMP) aims at predicting listed companies' sto...
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01/04/2022
Modeling Users' Behavior Sequences with Hierarchical Explainable Network for Cross-domain Fraud Detection
With the explosive growth of the e-commerce industry, detecting online t...
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01/04/2022
Aligning Domain-specific Distribution and Classifier for Cross-domain Classification from Multiple Sources
While Unsupervised Domain Adaptation (UDA) algorithms, i.e., there are o...
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01/04/2022
Multi-Representation Adaptation Network for Cross-domain Image Classification
In image classification, it is often expensive and time-consuming to acq...
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12/31/2021
Exploiting Bi-directional Global Transition Patterns and Personal Preferences for Missing POI Category Identification
Recent years have witnessed the increasing popularity of Location-based ...
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12/31/2021
Neural Hierarchical Factorization Machines for User's Event Sequence Analysis
Many prediction tasks of real-world applications need to model multi-ord...
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12/31/2021
Domain Adaptation with Category Attention Network for Deep Sentiment Analysis
Domain adaptation tasks such as cross-domain sentiment classification ai...
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12/31/2021
Modelling of Bi-directional Spatio-Temporal Dependence and Users' Dynamic Preferences for Missing POI Check-in Identification
Human mobility data accumulated from Point-of-Interest (POI) check-ins p...
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12/27/2021
Mind the Gap: Cross-Lingual Information Retrieval with Hierarchical Knowledge Enhancement
Cross-Lingual Information Retrieval (CLIR) aims to rank the documents wr...
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12/24/2021
Dual Hierarchical Attention Networks for Bi-typed Heterogeneous Graph Learning
Bi-typed heterogeneous graphs are applied in many real-world scenarios. ...
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12/01/2021
Domain-oriented Language Pre-training with Adaptive Hybrid Masking and Optimal Transport Alignment
Motivated by the success of pre-trained language models such as BERT in ...
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11/11/2021
Towards Robust Knowledge Graph Embedding via Multi-task Reinforcement Learning
Nowadays, Knowledge graphs (KGs) have been playing a pivotal role in AI-...
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10/29/2021
Deep Keyphrase Completion
Keyphrase provides accurate information of document content that is high...
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10/21/2021
Personalized Transfer of User Preferences for Cross-domain Recommendation
Cold-start problem is still a very challenging problem in recommender sy...
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10/21/2021
Improving Non-autoregressive Generation with Mixup Training
While pre-trained language models have achieved great success on various...
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06/16/2021
AMA-GCN: Adaptive Multi-layer Aggregation Graph Convolutional Network for Disease Prediction
Recently, Graph Convolutional Networks (GCNs) have proven to be a powerf...
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05/31/2021
Learning to Expand Audience via Meta Hybrid Experts and Critics for Recommendation and Advertising
In recommender systems and advertising platforms, marketers always want ...
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05/18/2021
Modeling the Sequential Dependence among Audience Multi-step Conversions with Multi-task Learning in Targeted Display Advertising
In most real-world large-scale online applications (e.g., e-commerce or ...
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05/11/2021
Learning to Warm Up Cold Item Embeddings for Cold-start Recommendation with Meta Scaling and Shifting Networks
Recently, embedding techniques have achieved impressive success in recom...
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05/11/2021
Transfer-Meta Framework for Cross-domain Recommendation to Cold-Start Users
Cold-start problems are enormous challenges in practical recommender sys...
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01/27/2021
Combat Data Shift in Few-shot Learning with Knowledge Graph
Many few-shot learning approaches have been designed under the meta-lear...
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01/18/2021
Modeling Heterogeneous Relations across Multiple Modes for Potential Crowd Flow Prediction
Potential crowd flow prediction for new planned transportation sites is ...
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01/09/2021
LightXML: Transformer with Dynamic Negative Sampling for High-Performance Extreme Multi-label Text Classification
Extreme Multi-label text Classification (XMC) is a task of finding the m...
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09/07/2020