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Found 8 papers, 2 papers with code
Implicit Relation Linking for Question Answering over Knowledge Graph
In this paper, we propose an implicit RL method called ImRL, which links relation phrases in NL to relation paths in KG.
Search Intenion Network for Personalized Query Auto-Completion in E-Commerce
Query Auto-Completion(QAC), as an important part of the modern search engine, plays a key role in complementing user queries and helping them refine their search intentions. Today's QAC systems in real-world scenarios face two major challenges:1)intention equivocality(IE): during the user's typing process, the prefix often contains a combination of characters and subwords, which makes the current intention ambiguous and difficult to model. 2)intention transfer (IT):previous works make personalized recommendations based on users' historical sequences, but ignore the search intention transfer. However, the current intention extracted from prefix may be contrary to the historical preferences.
Gaussian Graph with Prototypical Contrastive Learning in E-Commerce Bundle Recommendation
In this paper, we propose a novel Gaussian Graph with Prototypical Contrastive Learning (GPCL) framework to overcome these challenges.
Trustworthy Knowledge Graph Completion Based on Multi-sourced Noisy Data
In this paper, we propose a new trustworthy method that exploits facts for a KG based on multi-sourced noisy data and existing facts in the KG.
Metapaths guided Neighbors aggregated Network for?Heterogeneous Graph Reasoning
Specially, MHN employs node base embedding to encapsulate node attributes, BFS and DFS neighbors aggregation within a metapath to capture local and global information, and metapaths aggregation to combine different semantics of the heterogeneous graph.
Transformer-based Language Model Fine-tuning Methods for COVID-19 Fake News Detection
However, universal language models may perform weakly in these fake news detection for lack of large-scale annotated data and sufficient semantic understanding of domain-specific knowledge.
Spending Money Wisely: Online Electronic Coupon Allocation based on Real-Time User Intent Detection
We call this problem the coupon allocation problem.
Deep Match to Rank Model for Personalized Click-Through Rate Prediction
In User-to-Item Network, we represent the relevance between user and item by inner product of the corresponding representation in the embedding space.
