Papers Graph Matching
“Graph Matching” 태그가 달린 논문 515편 · 필터 해제
An Approach to Inference-Driven Dialogue Management within a Social Chatbot
We present a chatbot implementing a novel dialogue management approach based on logical inference. Instead of framing conversation a sequence of response generation tasks, we model conversation as a collaborative inferen…
ChatbotCollaborative InferenceDialogue ManagementGraph Matching+2Results of SemTab 2021
SemTab 2021 was the third edition of the Semantic Web Challenge on Tabular Data to Knowledge Graph Matching, successfully collocated with the 20th International Semantic Web Conference (ISWC) and the 16th Ontology Matchi…
Graph MatchingOntology MatchingTable annotationConvex Joint Graph Matching and Clustering via Semidefinite Relaxations
This paper proposes a new algorithm for simultaneous graph matching and clustering. For the first time in the literature, these two problems are solved jointly and synergetically without relying on any training data, whi…
ClusteringGraph MatchingGAMnet: Robust Feature Matching via Graph Adversarial-Matching Network
Recently, deep graph matching (GM) methods have gained increasing attention. These methods integrate graph nodes¡¯s embedding, node/edges¡¯s affinity learning and final correspondence solver together in an end-to-end man…
Graph MatchingProxy Graph Matching with Proximal Matching Networks
Estimating feature point correspondence is a common technique in computer vision. A line of recent data-driven approaches utilizing the graph neural networks improved the matching accuracy by a large margin. However, the…
Graph MatchingGraph Neural NetworkTAG: Toward Accurate Social Media Content Tagging with a Concept Graph
Although conceptualization has been widely studied in semantics and knowledge representation, it is still challenging to find the most accurate concept phrases to characterize the main idea of a text snippet on the fast-…
Dependency ParsingGraph MatchingNegationSentence+2Exact Matching of Random Graphs with Constant Correlation
This paper deals with the problem of graph matching or network alignment for Erd\H{o}s--R\'enyi graphs, which can be viewed as a noisy average-case version of the graph isomorphism problem. Let $G$ and $G'$ be $G(n, p)$ …
Graph MatchingSGMNet: Scene Graph Matching Network for Few-Shot Remote Sensing Scene Classification
Few-Shot Remote Sensing Scene Classification (FSRSSC) is an important task, which aims to recognize novel scene classes with few examples. Recently, several studies attempt to address the FSRSSC problem by following few-…
graph constructionGraph Matchingimage-classificationImage Classification+2Matching Models for Graph Retrieval
Graph Retrieval has witnessed continued interest and progress in the past few years. In thisreport, we focus on neural network based approaches for Graph matching and retrieving similargraphs from a corpus of graphs. We …
Graph MatchingRetrievalKepler-aSI at SemTab 2021
In this paper, we present our system Kepler-aSI, for the Semantic Web Challenge on Tabular Data to Knowledge Graph Matching (SemTab 2021). This system is participating for the second time in this campaign, bringing impro…
Cell Entity AnnotationColumn Type AnnotationGraph MatchingKnowledge Graphs+1MAGIC: Mining an Augmented Graph using INK, starting from a CSV
A large portion of structured data does not yet reap the benefits of the Semantic Web. Therefore, The “Tabular Data to Knowledge Graph Matching” competition at ISWC tries to bridge this gap by evaluating and promoting th…
Cell Entity AnnotationColumn Type AnnotationGraph MatchingTable annotationJenTab Meets SemTab 2021's New Challenges
While tables are a rich source of structured information, their automated use is oftentimes prevented by the inherent ambiguity contained within. Issues ranging from mere typos over inconsistent naming conventions to hom…
Cell Entity AnnotationColumn Type AnnotationGraph MatchingTable annotationSparse Quadratic Optimisation over the Stiefel Manifold with Application to Permutation Synchronisation
We address the non-convex optimisation problem of finding a sparse matrix on the Stiefel manifold (matrices with mutually orthogonal columns of unit length) that maximises (or minimises) a quadratic objective function. O…
ClusteringConstrained ClusteringGraph MatchingAn Analysis of Euclidean vs. Graph-Based Framing for Bilingual Lexicon Induction from Word Embedding Spaces
Much recent work in bilingual lexicon induction (BLI) views word embeddings as vectors in Euclidean space. As such, BLI is typically solved by finding a linear transformation that maps embeddings to a common space. Alter…
Bilingual Lexicon InductionGraph MatchingWord EmbeddingsOne-shot Key Information Extraction from Document with Deep Partial Graph Matching
Automating the Key Information Extraction (KIE) from documents improves efficiency, productivity, and security in many industrial scenarios such as rapid indexing and archiving. Many existing supervised learning methods …
Graph MatchingKey Information ExtractionMatching with Transformers in MELT
One of the strongest signals for automated matching of ontologies and knowledge graphs are the textual descriptions of the concepts. The methods that are typically applied (such as character- or token-based comparisons) …
Graph MatchingKnowledge GraphsOntology MatchingJoint Graph Learning and Matching for Semantic Feature Correspondence
In recent years, powered by the learned discriminative representation via graph neural network (GNN) models, deep graph matching methods have made great progresses in the task of matching semantic features. However, thes…
Graph LearningGraph MatchingGraph Neural NetworkWeisfeiler-Leman in the BAMBOO: Novel AMR Graph Metrics and a Benchmark for AMR Graph Similarity
Several metrics have been proposed for assessing the similarity of (abstract) meaning representations (AMRs), but little is known about how they relate to human similarity ratings. Moreover, the current metrics have comp…
AMR Graph SimilarityGraph MatchingGraph SimilaritySentence+1Learning to Match Features with Seeded Graph Matching Network
Matching local features across images is a fundamental problem in computer vision. Targeting towards high accuracy and efficiency, we propose Seeded Graph Matching Network, a graph neural network with sparse structure to…
Graph MatchingGraph Neural NetworkAdaptive Edge Attention for Graph Matching with Outliers
Graph matching aims at establishing correspondence between node sets of given graphs while keeping the consistency between their edge sets. However, outliers in practical scenarios and equivalent learning of edge represe…
Edge ClassificationGraph Matching