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Footprints of buildings can provide cues about architectural styles and functional types. Learning such latent thematic information from geometry is relevant for various applications, such as urban planning and map generalization. A common task in ...

Image-to-image retrieval, a fundamental task, aims at matching similar images based on a query image. Existing methods with convolutional neural networks are usually sensitive to low-level visual features, and ignore high-level semantic relationship ...

How do social networks differ across platforms? How do information networks change over time? Answering questions like these requires us to compare two or more graphs. This task is commonly treated as a measurement problem, but numerical answers give ...

Computing graph similarity is an important task in many graph-related applications such as retrieval in graph databases or graph clustering. While numerous measures have been proposed to capture the similarity between a pair of graphs, Graph Edit ...

Analysis of morphological data is central to a broad class of scientific problems in materials science, astronomy, bio-medicine, and many others. Understanding relationships between morphologies is a core analytical task in such settings. In this paper,...

In this paper we present a graph-based framework that, utilizing relations between groups of System-calls, detects whether an unknown software sample is malicious or benign, and classifies a malicious software to one of a set of known malware families. In ...

The problem of accurately measuring the similarity between graphs is at the core of many applications in a variety of disciplines. Graph kernels have recently emerged as a promising approach to this problem. There are now many kernels, each focusing on ...

We propose an end-to-end graph similarity learning framework called Higher-order Siamese GCN for multi-subject fMRI data analysis. The proposed framework learns the brain network representations via a supervised metric-based approach with siamese neural ...

Nondeterminism is an increasingly entrenched property of high-performance computing (HPC) applications and has recently been shown to seriously hamper debugging and reproducibility efforts. Tools for addressing the nondeterministic debugging problem have ...

Determining the similarity between two objects is pertinent to many applications. When the basis for similarity is a set of object-to-object relationships, it is natural to rely on graph-theoretic measures. One seminal technique for measuring the ...

Comparison among graphs is ubiquitous in graph analytics. However, it is a hard task in terms of the expressiveness of the employed similarity measure and the efficiency of its computation. Ideally, graph comparison should be invariant to the order of ...

Graph similarity can contribute to the solutions of a wide variety of real-life problems. Effective graph similarity measures, therefore, are in high demand in areas such as communication network, biology, medicine, finance, etc. Existing similarity ...

Web-scale information networks containing billions of entities are common nowadays. Querying these networks can be modeled as a subgraph matching problem. Since information networks are incomplete and noisy in nature, it is important to discover answers ...

A mission plan consists of a set of actions to be performed in a given situation such that the specified actions mitigate the assessed situation effectively. Military missions use sensors of diverse sensing modalities for Intelligence, Reconnaissance ...

The drastic increase of Android malware has led to a strong interest in developing methods to automate the malware analysis process. Existing automated Android malware detection and classification methods fall into two general categories: 1) signature-...

The study of the topological structure of complex networks has fascinated researchers for several decades, and today we have a fairly good understanding of the types and reoccurring characteristics of many different complex networks. However, ...

One of the most fundamental problem that we face in the graph domain is that of establishing the similarity, or alternatively the distance, between graphs. In this paper, we address the problem of measuring the similarity between attributed graphs. In ...

SimRank has become an important similarity measure to rank web documents based on a graph model on hyperlinks. The existing approaches for conducting SimRank computation adopt an iteration paradigm. The most efficient deterministic technique yields $O\left(n^3\right)$ ...

The folksonomies resulting from user-generated tag systems feature rapid adaptability, and reflect the information needs of their supporting user communities. However, they suffer from well-known problems, such as polysemy, heteronymy and lack of recall,...

Modern software project repositories provide support for both source code and design models that describe in details the data structure, behavior, and components of an application. We propose a graph matching-based technique between software models to ...