Papers Graph Matching

Attributed Graph Mining and Matching: An Attempt to Define and Extract Soft Attributed Patterns

Graph matching and graph mining are two typical areas in artificial intelligence. In this paper, we define the soft attributed pattern (SAP) to describe the common subgraph pattern among a set of attributed relational gr…

Finding Matches in a Haystack: A Max-Pooling Strategy for Graph Matching in the Presence of Outliers

A major challenge in real-world feature matching problems is to tolerate the numerous outliers arising in typical visual tasks. Variations in object appearance, shape, and structure within the same object class make it h…

Symmetry-Aware Nonrigid Matching of Incomplete 3D Surfaces

We present a nonrigid shape matching technique for establishing correspondences of incomplete 3D surfaces that exhibit intrinsic reflectional symmetry. The key for solving the symmetry ambiguity problem is to use a point…

Probabilistic Labeling for Efficient Referential Grounding based on Collaborative Discourse

DEM Registration and Error Analysis using ASCII values

Digital Elevation Model (DEM), while providing a bare earth look, is heavily used in many applications including construction modeling, visualization, and GIS. Their registration techniques have not been explored much. M…

Geometric Polynomial Constraints in Higher-Order Graph Matching

Correspondence is a ubiquitous problem in computer vision and graph matching has been a natural way to formalize correspondence as an optimization problem. Recently, graph matching solvers have included higher-order term…

Graph Matching: Relax at Your Own Risk

Graph matching---aligning a pair of graphs to minimize their edge disagreements---has received wide-spread attention from both theoretical and applied communities over the past several decades, including combinatorics, c…

Shiva++: An Enhanced Graph based Ontology Matcher

With the web getting bigger and assimilating knowledge about different concepts and domains, it is becoming very difficult for simple database driven applications to capture the data for a domain. Thus developers have co…

Principled Graph Matching Algorithms for Integrating Multiple Data Sources

This paper explores combinatorial optimization for problems of max-weight graph matching on multi-partite graphs, which arise in integrating multiple data sources. Entity resolution-the data integration problem of perfor…

Graph matching: relax or not?

We consider the problem of exact and inexact matching of weighted undirected graphs, in which a bijective correspondence is sought to minimize a quadratic weight disagreement. This computationally challenging problem is …

Seeded Graph Matching Via Joint Optimization of Fidelity and Commensurability

We present a novel approximate graph matching algorithm that incorporates seeded data into the graph matching paradigm. Our Joint Optimization of Fidelity and Commensurability (JOFC) algorithm embeds two graphs into a co…

Large-scale Semantic Parsing without Question-Answer Pairs

In this paper we introduce a novel semantic parsing approach to query Freebase in natural language without requiring manual annotations or question-answer pairs. Our key insight is to represent natural language via seman…

Robust Multimodal Graph Matching: Sparse Coding Meets Graph Matching

Graph matching is a challenging problem with very important applications in a wide range of fields, from image and video analysis to biological and biomedical problems. We propose a robust graph matching algorithm inspir…

Skin Segmentation based Elastic Bunch Graph Matching for efficient multiple Face Recognition

This paper is aimed at developing and combining different algorithms for face detection and face recognition to generate an efficient mechanism that can detect and recognize the facial regions of input image. For the det…

Spectral Clustering for Divide-and-Conquer Graph Matching

We present a parallelized bijective graph matching algorithm that leverages seeds and is designed to match very large graphs. Our algorithm combines spectral graph embedding with existing state-of-the-art seeded graph ma…

GNCGCP - Graduated NonConvexity and Graduated Concavity Procedure

In this paper we propose the Graduated NonConvexity and Graduated Concavity Procedure (GNCGCP) as a general optimization framework to approximately solve the combinatorial optimization problems on the set of partial perm…

Smatch: an Evaluation Metric for Semantic Feature Structures

Generalizing an Approximate Subgraph Matching-based System to Extract Events in Molecular Biology and Cancer Genetics

Exploring a Probabilistic Earley Parser for Event Composition in Biomedical Texts

Modeling Collaborative Referring for Situated Referential Grounding