Improved search-tree algorithms for the cluster edit problem. (c2011)

Includes bibliographical references (leaves 25-26).

Saved in:
Bibliographic Details
Main Author: Ghrayeb, Ali Kassem (author)
Format: masterThesis
Published: 2011
Subjects:
Online Access:http://hdl.handle.net/10725/997
https://doi.org/10.26756/th.2011.22
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1864513455701098496
author Ghrayeb, Ali Kassem
author_facet Ghrayeb, Ali Kassem
author_role author
dc.creator.none.fl_str_mv Ghrayeb, Ali Kassem
dc.date.none.fl_str_mv 2011-11-17T09:33:03Z
2011-11-17T09:33:03Z
2011
2011-11-17
2011-05-30
dc.identifier.none.fl_str_mv http://hdl.handle.net/10725/997
https://doi.org/10.26756/th.2011.22
dc.language.none.fl_str_mv en
dc.publisher.none.fl_str_mv Lebanese American University
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Pattern recognition systems
Mathematics -- Data processing
Artificial intelligence
dc.title.none.fl_str_mv Improved search-tree algorithms for the cluster edit problem. (c2011)
dc.type.none.fl_str_mv Thesis
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/masterThesis
description Includes bibliographical references (leaves 25-26).
eu_rights_str_mv openAccess
format masterThesis
id LAURepo_e0e5aed93d28253f51acd2f8e451fc39
language_invalid_str_mv en
network_acronym_str LAURepo
network_name_str Lebanese American University repository
oai_identifier_str oai:laur.lau.edu.lb:10725/997
publishDate 2011
publisher.none.fl_str_mv Lebanese American University
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
spelling Improved search-tree algorithms for the cluster edit problem. (c2011)Ghrayeb, Ali KassemPattern recognition systemsMathematics -- Data processingArtificial intelligenceIncludes bibliographical references (leaves 25-26).In the Cluster Edit problem, we are asked to transform a given graph into a transitive graph, via edge deletion or addition operations, to make sure that the vertices are partitioned into a disjoint union of cliques. Cluster Edit finds application in a number of domains, including computational biology and social networks. When parameterized by the number of permitted edge-edit operation (k), the problem can be solved in O (3k) time via a search-tree backtracking strategy. The current fastest worstcase fixed-parameter algorithm described in [7] adopts the same strategy and solves Cluster Edit in O (1.82k). This thesis presents new techniques to enhance any search tree- based algorithm for the Cluster Edit problem. These techniques, which include new heuristics and impose bounds on allowable edge operations per vertex, cause effective pruning of search-trees and yield noticeable improvements in experimental running times on almost all types of input instances.1 bound copy: x, 26 leaves; 30 cm. available at RNL.Lebanese American University2011-11-17T09:33:03Z2011-11-17T09:33:03Z20112011-11-172011-05-30Thesisinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesishttp://hdl.handle.net/10725/997https://doi.org/10.26756/th.2011.22eninfo:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/9972020-05-18T14:53:53Z
spellingShingle Improved search-tree algorithms for the cluster edit problem. (c2011)
Ghrayeb, Ali Kassem
Pattern recognition systems
Mathematics -- Data processing
Artificial intelligence
status_str publishedVersion
title Improved search-tree algorithms for the cluster edit problem. (c2011)
title_full Improved search-tree algorithms for the cluster edit problem. (c2011)
title_fullStr Improved search-tree algorithms for the cluster edit problem. (c2011)
title_full_unstemmed Improved search-tree algorithms for the cluster edit problem. (c2011)
title_short Improved search-tree algorithms for the cluster edit problem. (c2011)
title_sort Improved search-tree algorithms for the cluster edit problem. (c2011)
topic Pattern recognition systems
Mathematics -- Data processing
Artificial intelligence
url http://hdl.handle.net/10725/997
https://doi.org/10.26756/th.2011.22