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LegalGNN: Legal Information Enhanced Graph Neural Network for Recommendation
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-030-29551-6_56openalex-snapshot
Building Chinese Legal Hybrid Knowledge Network
inferredcites →https://doi.org/10.1007/978-3-319-58451-5_13openalex-snapshot
Building and Processing a Knowledge-Graph for Legal Data
inferredcites →https://doi.org/10.1007/978-3-319-93417-4_38openalex-snapshot
Modeling Relational Data with Graph Convolutional Networks
inferredcites →https://doi.org/10.1007/978-981-15-0118-0_7openalex-snapshot
A Content-Based Recommendation Framework for Judicial Cases
inferredcites →https://doi.org/10.1109/tits.2019.2950416openalex-snapshot
Traffic Graph Convolutional Recurrent Neural Network: A Deep Learning Framework for Network-Scale Traffic Learning and Forecasting
inferredcites →https://doi.org/10.1109/tkde.2017.2766059openalex-snapshot
A Location-Query-Browse Graph for Contextual Recommendation
inferredcites →https://doi.org/10.1109/tkde.2018.2833443openalex-snapshot
Heterogeneous Information Network Embedding for Recommendation
inferredcites →https://doi.org/10.1145/2988450.2988454openalex-snapshot
Wide & Deep Learning for Recommender Systems
inferredcites →https://doi.org/10.1145/3077136.3080777openalex-snapshot
Neural Factorization Machines for Sparse Predictive Analytics
inferredcites →https://doi.org/10.1145/3077136.3080797openalex-snapshot
Attentive Collaborative Filtering
inferredcites →https://doi.org/10.1145/3124749.3124754openalex-snapshot
Deep & Cross Network for Ad Click Predictions
inferredcites →https://doi.org/10.1145/3209978.3210032openalex-snapshot
Cross-language Citation Recommendation via Hierarchical Representation Learning on Heterogeneous Graph
inferredcites →https://doi.org/10.1145/3269206.3271710openalex-snapshot
Attention-based Adaptive Model to Unify Warm and Cold Starts Recommendation
inferredcites →https://doi.org/10.1145/3292500.3330836openalex-snapshot
Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems
inferredcites →https://doi.org/10.1145/3292500.3330964openalex-snapshot
Representation Learning for Attributed Multiplex Heterogeneous Network
inferredcites →https://doi.org/10.1145/3394486.3403177openalex-snapshot
AM-GCN: Adaptive Multi-channel Graph Convolutional Networks
inferredcites →https://doi.org/10.1145/582415.582418openalex-snapshot
Cumulated gain-based evaluation of IR techniques
inferredcites →https://doi.org/10.1609/aaai.v29i1.9491openalex-snapshot
Learning Entity and Relation Embeddings for Knowledge Graph Completion
inferredcites →https://doi.org/10.18653/v1/d19-1493openalex-snapshot
Neural News Recommendation with Heterogeneous User Behavior
inferredcites →https://doi.org/10.18653/v1/d19-1671openalex-snapshot
Neural News Recommendation with Multi-Head Self-Attention
inferredcites →https://doi.org/10.18653/v1/n19-1423openalex-snapshot
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
inferredcites →https://doi.org/10.24963/ijcai.2018/484openalex-snapshot
Your Tweets Reveal What You Like: Introducing Cross-media Content Information into Multi-domain Recommendation
inferredcites →https://doi.org/10.24963/ijcai.2019/592openalex-snapshot
STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems
inferredcites →https://doi.org/10.24963/ijcai.2020/484openalex-snapshot
BERT-PLI: Modeling Paragraph-Level Interactions for Legal Case Retrieval
inferredcites →https://doi.org/10.3233/978-1-61499-726-9-131openalex-snapshot
Making a Cold Start in Legal Recommendation: An Experiment
inferredcites →https://doi.org/10.48550/arxiv.1904.09675openalex-snapshot
BERTScore: Evaluating Text Generation with BERT
inferredcites →https://doi.org/10.48550/arxiv.1911.07673openalex-snapshot
Using Mapping Languages for Building Legal Knowledge Graphs from XML Files
inferredcites →https://doi.org/10.5220/0006900000510060openalex-snapshot
Graph Convolutional Matrix Completion for Bipartite Edge Prediction
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-031-29168-5_7openalex-snapshot
nigam@COLIEE-22: Legal Case Retrieval and Entailment Using Cascading of Lexical and Semantic-Based Models
inferred← citeshttps://doi.org/10.1007/978-3-031-44696-2_43openalex-snapshot
Enhancing Similar Case Matching with Event-Context Detection in Legal Intelligence
inferred← citeshttps://doi.org/10.1007/978-3-031-56060-6_6openalex-snapshot
CaseGNN: Graph Neural Networks for Legal Case Retrieval with Text-Attributed Graphs
inferred← citeshttps://doi.org/10.1007/978-3-031-88714-7_6openalex-snapshot
Leveraging Query Terms for Efficient Legal Document Recommendation
inferred← citeshttps://doi.org/10.1007/978-981-99-1600-9_11openalex-snapshot
Legal Knowledge Representation Learning
inferred← citeshttps://doi.org/10.1007/s10489-022-03337-2openalex-snapshot
GA-GWNN: Detecting anomalies of online learners by granular computing and graph wavelet convolutional neural network
inferred← citeshttps://doi.org/10.1007/s10489-025-06818-2openalex-snapshot
Uncovering connections: a reference network approach to statute law retrieval
inferred← citeshttps://doi.org/10.1007/s10506-023-09377-4openalex-snapshot
Integrating legal event and context information for Chinese similar case analysis
inferred← citeshttps://doi.org/10.1007/s10506-023-09378-3openalex-snapshot
A large scale benchmark for session-based recommendations on the legal domain
inferred← citeshttps://doi.org/10.1007/s10506-023-09385-4openalex-snapshot
Automating petition classification in Brazil’s legal system: a two-step deep learning approach
inferred← citeshttps://doi.org/10.1007/s10506-025-09479-1openalex-snapshot
ARDI: a new dataset for automatic advocate recommendation in the Indian Legal System
inferred← citeshttps://doi.org/10.1007/s10506-025-09493-3openalex-snapshot
Providing legal pincite recommendations using language representations
inferred← citeshttps://doi.org/10.1007/s10506-025-09494-2openalex-snapshot
Challenges and Opportunities for Visual Analytics in Jurisprudence
inferred← citeshttps://doi.org/10.1007/s11257-023-09359-wopenalex-snapshot
Recommending on graphs: a comprehensive review from a data perspective
inferred← citeshttps://doi.org/10.1007/s12599-024-00886-3openalex-snapshot
Ontology-Driven Automated Reasoning About Property Crimes
inferred← citeshttps://doi.org/10.1016/j.aei.2025.104144openalex-snapshot
Construction case-relevant article-level law identification using fine-tuned large language models: A study in China’s construction industry
inferred← citeshttps://doi.org/10.1016/j.aiopen.2024.09.002openalex-snapshot
Large language models in law: A survey
inferred← citeshttps://doi.org/10.1016/j.eswa.2021.116311openalex-snapshot
Modeling behavior sequence for personalized fund recommendation with graphical deep collaborative filtering
inferred← citeshttps://doi.org/10.1016/j.ipm.2023.103560openalex-snapshot
A hierarchical convolutional model for biomedical relation extraction
inferred← citeshttps://doi.org/10.1016/j.knosys.2025.113964openalex-snapshot
Multi-granular legal information fusion with adversarial compensation: A hierarchical and logic-aware framework for robust case retrieval
inferred← citeshttps://doi.org/10.1109/bigdata59044.2023.10386684openalex-snapshot
Graph-Based Approach for European Law Classification
inferred← citeshttps://doi.org/10.1109/bigdata62323.2024.10826025openalex-snapshot
EuropeanLawAdvisor: an open source search engine for European laws
inferred← citeshttps://doi.org/10.1109/ijcnn54540.2023.10191443openalex-snapshot
ReGRL: An Informative Graph Representation via Hierarchical Recursive Learning for Legal Case Recommendation
inferred← citeshttps://doi.org/10.1109/ocit65031.2024.00019openalex-snapshot
Multiple Graph-Based Approach to Recommend Domain-Dependent Documents
inferred← citeshttps://doi.org/10.1109/tii.2022.3203395openalex-snapshot
Federated Learning-Based Cross-Enterprise Recommendation With Graph Neural Networks
inferred← citeshttps://doi.org/10.1111/exsy.70073openalex-snapshot
On the Significance of Graph Neural Networks With Pretrained Transformers in Content‐Based Recommender Systems for Academic Article Classification
inferred← citeshttps://doi.org/10.1145/3544105openalex-snapshot
Adversarial Auto-encoder Domain Adaptation for Cold-start Recommendation with Positive and Negative Hypergraphs
inferred← citeshttps://doi.org/10.1145/3567420openalex-snapshot
Poisoning GNN-based Recommender Systems with Generative Surrogate-based Attacks
inferred← citeshttps://doi.org/10.1145/3592853openalex-snapshot
Multi-View Enhanced Graph Attention Network for Session-Based Music Recommendation
inferred← citeshttps://doi.org/10.1145/3603374openalex-snapshot
Stylized Data-to-text Generation: A Case Study in the E-Commerce Domain
inferred← citeshttps://doi.org/10.1145/3604558openalex-snapshot
Fairness in Recommender Systems: Evaluation Approaches and Assurance Strategies
inferred← citeshttps://doi.org/10.1145/3611385openalex-snapshot
SLED: Structure Learning based Denoising for Recommendation
inferred← citeshttps://doi.org/10.1145/3626772.3657693openalex-snapshot
CaseLink: Inductive Graph Learning for Legal Case Retrieval
inferred← citeshttps://doi.org/10.1145/3628602openalex-snapshot
Measuring and Mitigating Gender Bias in Legal Contextualized Language Models
inferred← citeshttps://doi.org/10.1145/3633202openalex-snapshot
Privacy-Preserving Individual-Level COVID-19 Infection Prediction via Federated Graph Learning
inferred← citeshttps://doi.org/10.1145/3750724openalex-snapshot
Semantic Relation Guided Dual-view Contrastive Learning for Session-based Recommendations
inferred← citeshttps://doi.org/10.1145/3816732openalex-snapshot
Cassette: Case-to-Case Structural Distillation for Efficient Legal Case Retrieval
inferred← citeshttps://doi.org/10.35699/2965-6931.2023.47689openalex-snapshot
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