Titlebook: ;

Limerick

Experimental Evaluation of Subgraph Isomorphism Solvers,f a pattern graph into a target graph. In the pattern recognition community, the most well-known SI solvers are VF2, VF3, and RI. SI is also widely studied in the constraint programming community, and many constraint-based SI solvers have been proposed since Ullman, such as LAD and Glasgow, for exam

聯(lián)想記憶

GEDLIB: A C++ Library for Graph Edit Distance Computation,resent GEDLIB, a C++ library for exactly or approximately computing .. Many existing algorithms for . are already implemented in GEDLIB. Moreover, GEDLIB is designed to be easily extensible: for implementing new edit cost functions and . algorithms, it suffices to implement abstract classes containe

木訥

dissolution

Sub-optimal Graph Matching by Node-to-Node Assignment Classification,een presented. Nevertheless, these algorithms usually cannot be used in real applications due to runtime restrictions. For this reason, other graph-matching algorithms have also been used that compute an approximation of the graph correspondence with lower runtime. Clearly, in a real application, th

ILEUM

Cross-Evaluation of Graph-Based Keyword Spotting in Handwritten Historical Documents,e to adapt their size and structure to the individual handwriting and represent binary relationships that might exist within the handwriting. We observe an increasing number of graph-based keyword spotting frameworks in the last years. In general, keyword spotting allows to retrieve instances of an

煞費(fèi)苦心

FECK

Solving the Graph Edit Distance Problem with Variable Partitioning Local Search,oblem. This paper presents an adapted version of . (VPLS) matheuristic for solving the GED problem. The main idea in VPLS is to perform local searches in the solution space of a . (MILP). A local search is done in a small neighborhood defined based on a set of special variables. Those special variab

CIS

仲裁者

Event Prediction Based on Unsupervised Graph-Based Rank-Fusion Models,nks of a query, defined according to different criteria, into a graph. Later, we embed the generated graph into a feature space, creating fusion vectors. These vectors are then used to train a predictor to determine if an input (even multimodal) object refers to an event or not. Performed experiment

hegemony

Generalized Median Graph via Iterative Alternate Minimizations, for simple classes of graphs. In this paper, we propose an efficient approach based on block coordinate descent to compute a generalized median graph from a set of graphs. This approach relies on a clear definition of the optimization process and handles labeling on both edges and nodes. This itera