Papers Graph Ranking
“Graph Ranking” 태그가 달린 논문 19편 · 필터 해제
Target-Oriented Pretraining Data Selection via Neuron-Activated Graph
Everyday tasks come with a target, and pretraining models around this target is what turns them into experts. In this paper, we study target-oriented language model (LM) pretraining by introducing Neuron-Activated Graph …
Graph RankingPersonalized Ranking on Cascading Behavior Graphs for Accurate Multi-Behavior Recommendation
Multi-behavior recommendation predicts items a user may purchase by analyzing diverse behaviors like viewing, adding to a cart, and purchasing. Existing methods fall into two categories: representation learning and graph…
Graph RankingRepresentation LearningAdvanced Academic Team Worker Recommendation Models
Collaborator recommendation is an important task in academic domain. Most of the existing approaches have the assumption that the recommendation system only need to recommend a specific researcher for the task. However, …
Graph RankingGraph Ranking Contrastive Learning: A Extremely Simple yet Efficient Method
Graph contrastive learning (GCL) has emerged as a representative graph self-supervised method, achieving significant success. The currently prevalent optimization objective for GCL is InfoNCE. Typically, it employs augme…
Contrastive LearningGraph LearningGraph RankingToDD: Topological Compound Fingerprinting in Computer-Aided Drug Discovery
In computer-aided drug discovery (CADD), virtual screening (VS) is used for identifying the drug candidates that are most likely to bind to a molecular target in a large library of compounds. Most VS methods to date have…
Drug DiscoveryGraph RankingTripletGUSUM: Graph-based Unsupervised Summarization Using Sentence Features Scoring and Sentence-BERT
Unsupervised extractive document summarization aims to extract salient sentences from a document without requiring a labelled corpus. In existing graph-based methods, vertex and edge weights are usually created by calcul…
Document SummarizationExtractive Document SummarizationExtractive Text SummarizationGraph Ranking+5A Method of Query Graph Reranking for Knowledge Base Question Answering
This paper presents a novel reranking method to better choose the optimal query graph, a sub-graph of knowledge graph, to retrieve the answer for an input question in Knowledge Base Question Answering (KBQA). Existing me…
Graph RankingKnowledge Base Question AnsweringQuestion AnsweringRerankingGUSUM: Graph-Based Unsupervised Summarization using Sentence-BERT and Sentence Features
Unsupervised extractive document summarization aims to extract salient sentences from a document without requiring a labelled corpus. In existing graph-based methods, vertex and edge weights are mostly created by calcula…
Document SummarizationExtractive Document SummarizationExtractive Text SummarizationGraph Ranking+5Outlining and Filling: Hierarchical Query Graph Generation for Answering Complex Questions over Knowledge Graphs
Query graph construction aims to construct the correct executable SPARQL on the KG to answer natural language questions. Although recent methods have achieved good results using neural network-based query graph ranking, …
graph constructionGraph GenerationGraph RankingKnowledge Base Question Answering+1Ranking Structured Objects with Graph Neural Networks
Graph neural networks (GNNs) have been successfully applied in many structured data domains, with applications ranging from molecular property prediction to the analysis of social networks. Motivated by the broad applica…
Graph RankingGraph RegressionLearning-To-RankMolecular Property Prediction+1Addressing Time Bias in Bipartite Graph Ranking for Important Node Identification
The goal of the ranking problem in networks is to rank nodes from best to worst, according to a chosen criterion. In this work, we focus on ranking the nodes according to their quality. The problem of ranking the nodes i…
Graph RankingLearning to Rank Query Graphs for Complex Question Answering over Knowledge Graphs
In this paper, we conduct an empirical investigation of neural query graph ranking approaches for the task of complex question answering over knowledge graphs. We experiment with six different ranking models and propose …
Graph RankingKnowledge GraphsLearning-To-RankQuestion Answering+1Temporal Coherent and Graph Optimized Manifold Ranking for Visual Tracking
Recently, weighted patch representation has been widely studied for alleviating the impact of background information included in bounding box to improve visual tracking results. However, existing weighted patch represent…
Graph RankingVisual TrackingGraph Centrality Measures for Boosting Popularity-Based Entity Linking
Many Entity Linking systems use collective graph-based methods to disambiguate the entity mentions within a document. Most of them have focused on graph construction and initial weighting of the candidate entities, less …
Entity Linkinggraph constructionGraph RankingSCIR-QA at SemEval-2017 Task 3: CNN Model Based on Similar and Dissimilar Information between Keywords for Question Similarity
We describe a method of calculating the similarity of questions in community QA. Question in cQA are usually very long and there are a lot of useless information about calculating the similarity of questions. Therefore,w…
Community Question AnsweringGraph RankingInformation RetrievalKeyword Extraction+2A Graph Framework for Multimodal Medical Information Processing
Multimodal medical information processing is currently the epicenter of intense interdisciplinary research, as proper data fusion may lead to more accurate diagnoses. Moreover, multimodality may disambiguate cases of co-…
Graph Ranking