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Depth first search and linear graph algorithms

by Robert Tarjan - SIAM JOURNAL ON COMPUTING , 1972
"... The value of depth-first search or "backtracking" as a technique for solving problems is illustrated by two examples. An improved version of an algorithm for finding the strongly connected components of a directed graph and ar algorithm for finding the biconnected components of an undirect ..."
Abstract - Cited by 1406 (19 self) - Add to MetaCart
The value of depth-first search or "backtracking" as a technique for solving problems is illustrated by two examples. An improved version of an algorithm for finding the strongly connected components of a directed graph and ar algorithm for finding the biconnected components

Tabu Search -- Part I

by Fred Glover , 1989
"... This paper presents the fundamental principles underlying tabu search as a strategy for combinatorial optimization problems. Tabu search has achieved impressive practical successes in applications ranging from scheduling and computer channel balancing to cluster analysis and space planning, and more ..."
Abstract - Cited by 680 (11 self) - Add to MetaCart
This paper presents the fundamental principles underlying tabu search as a strategy for combinatorial optimization problems. Tabu search has achieved impressive practical successes in applications ranging from scheduling and computer channel balancing to cluster analysis and space planning

Fast Planning Through Planning Graph Analysis

by Avrim L. Blum, Merrick L. Furst - ARTIFICIAL INTELLIGENCE , 1995
"... We introduce a new approach to planning in STRIPS-like domains based on constructing and analyzing a compact structure we call a Planning Graph. We describe a new planner, Graphplan, that uses this paradigm. Graphplan always returns a shortest possible partial-order plan, or states that no valid pla ..."
Abstract - Cited by 1171 (3 self) - Add to MetaCart
We introduce a new approach to planning in STRIPS-like domains based on constructing and analyzing a compact structure we call a Planning Graph. We describe a new planner, Graphplan, that uses this paradigm. Graphplan always returns a shortest possible partial-order plan, or states that no valid

gSpan: Graph-Based Substructure Pattern Mining

by Xifeng Yan, Jiawei Han , 2002
"... We investigate new approaches for frequent graph-based pattern mining in graph datasets and propose a novel algorithm called gSpan (graph-based Substructure pattern mining) , which discovers frequent substructures without candidate generation. gSpan builds a new lexicographic order among graphs, and ..."
Abstract - Cited by 650 (34 self) - Add to MetaCart
, and maps each graph to a unique minimum DFS code as its canonical label. Based on this lexicographic order, gSpan adopts the depth-first search strategy to mine frequent connected subgraphs efficiently. Our performance study shows that gSpan substantially outperforms previous algorithms, sometimes

Search and replication in unstructured peer-to-peer networks

by Qin Lv, Pei Cao, Edith Cohen, Kai Li, Scott Shenker , 2002
"... Abstract Decentralized and unstructured peer-to-peer networks such as Gnutella are attractive for certain applicationsbecause they require no centralized directories and no precise control over network topologies and data placement. However, the flooding-based query algorithm used in Gnutella does n ..."
Abstract - Cited by 692 (6 self) - Add to MetaCart
. Finally, we find that among the various network topologies we consider, uniform random graphs yield the bestperformance. 1 Introduction The computer science community has become accustomed to the Internet's continuing rapid growth, but even tosuch jaded observers the explosive increase in Peer

Graphcut textures: Image and video synthesis using graph cuts

by Vivek Kwatra, Arno Schödl, Irfan Essa, Greg Turk, Aaron Bobick - ACM Transactions on Graphics, SIGGRAPH 2003 , 2003
"... This banner was generated by merging the source images in Figure 6 using our interactive texture merging technique. In this paper we introduce a new algorithm for image and video texture synthesis. In our approach, patch regions from a sample image or video are transformed and copied to the output a ..."
Abstract - Cited by 490 (9 self) - Add to MetaCart
. Unlike dynamic programming, our graph cut technique for seam optimization is applicable in any dimension. We specifically explore it in 2D and 3D to perform video texture synthesis in addition to regular image synthesis. We present approximative offset search techniques that work well in conjunction

Stochastic local search . . . -- Graph Colouring . . .

by Marco Chiarandini , 2005
"... This thesis is about advances in the application of Stochastic Local Search methods for solving graph colouring problems and highly constrained combinatorial optimisation problems that arise from real world systems. ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
This thesis is about advances in the application of Stochastic Local Search methods for solving graph colouring problems and highly constrained combinatorial optimisation problems that arise from real world systems.

Searching graphs with large clique number

by Boting Yang, Danny Dyer, Brian Alspach , 2006
"... ..."
Abstract - Cited by 1 (1 self) - Add to MetaCart
Abstract not found

Scaling Personalized Web Search

by Glen Jeh, Jennifer Widom - In Proceedings of the Twelfth International World Wide Web Conference , 2002
"... Recent web search techniques augment traditional text matching with a global notion of "importance" based on the linkage structure of the web, such as in Google's PageRank algorithm. For more refined searches, this global notion of importance can be specialized to create personalized ..."
Abstract - Cited by 409 (2 self) - Add to MetaCart
Recent web search techniques augment traditional text matching with a global notion of "importance" based on the linkage structure of the web, such as in Google's PageRank algorithm. For more refined searches, this global notion of importance can be specialized to create personalized

A New Method for Solving Hard Satisfiability Problems

by Bart Selman, Hector Levesque, David Mitchell - AAAI , 1992
"... We introduce a greedy local search procedure called GSAT for solving propositional satisfiability problems. Our experiments show that this procedure can be used to solve hard, randomly generated problems that are an order of magnitude larger than those that can be handled by more traditional approac ..."
Abstract - Cited by 730 (21 self) - Add to MetaCart
We introduce a greedy local search procedure called GSAT for solving propositional satisfiability problems. Our experiments show that this procedure can be used to solve hard, randomly generated problems that are an order of magnitude larger than those that can be handled by more traditional
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