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dc.contributor.authorBarth, L.en
dc.contributor.authorFabrikant, S. I.en
dc.contributor.authorKobourov, S. G.en
dc.contributor.authorLubiw, A.en
dc.contributor.authorNöllenburg, M.en
dc.contributor.authorOkamoto, Y.en
dc.contributor.authorPupyrev, S.en
dc.contributor.authorSquarcella, C.en
dc.contributor.authorUeckerdt, T.en
dc.contributor.authorWolff, A.en
dc.date.accessioned2021-08-31T15:03:43Z-
dc.date.available2021-08-31T15:03:43Z-
dc.date.issued2014-
dc.identifier.citationSemantic word cloud representations: Hardness and approximation algorithms / L. Barth, S. I. Fabrikant, S. G. Kobourov, et al. — DOI 10.1007/978-3-642-54423-1_45 // Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). — 2014. — Vol. 8392 LNCS. — P. 514-525.en
dc.identifier.isbn9783642544224-
dc.identifier.issn3029743-
dc.identifier.otherFinal2
dc.identifier.otherAll Open Access, Green3
dc.identifier.otherhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84899939512&doi=10.1007%2f978-3-642-54423-1_45&partnerID=40&md5=ce61aac9f628b4ec8129b1d6addd3750
dc.identifier.otherhttp://arxiv.org/pdf/1311.4778m
dc.identifier.urihttp://elar.urfu.ru/handle/10995/102462-
dc.description.abstractWe study a geometric representation problem, where we are given a set of axis-aligned rectangles (boxes) with fixed dimensions and a graph with vertex set. The task is to place the rectangles without overlap such that two rectangles touch if the graph contains an edge between them. We call this problem Contact Representation of Word Networks (Crown). It formalizes the geometric problem behind drawing word clouds in which semantically related words are close to each other. Here, we represent words by rectangles and semantic relationships by edges. We show that Crown is strongly NP-hard even if restricted to trees and weakly NP-hard if restricted to stars. We also consider the optimization problem Max-Crown where each adjacency induces a certain profit and the task is to maximize the sum of the profits. For this problem, we present constant-factor approximations for several graph classes, namely stars, trees, planar graphs, and graphs of bounded degree. Finally, we evaluate the algorithms experimentally and show that our best method improves upon the best existing heuristic by 45%. © 2014 Springer-Verlag Berlin Heidelberg.en
dc.format.mimetypeapplication/pdfen
dc.language.isoenen
dc.publisherSpringer Verlagen
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.sourceLect. Notes Comput. Sci.2
dc.sourceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en
dc.subjectAPPROXIMATION ALGORITHMSen
dc.subjectDATA MININGen
dc.subjectFORESTRYen
dc.subjectGEOMETRYen
dc.subjectHEURISTIC ALGORITHMSen
dc.subjectHEURISTIC METHODSen
dc.subjectINFORMATION SCIENCEen
dc.subjectPROFITABILITYen
dc.subjectSEMANTICSen
dc.subjectSTARSen
dc.subjectBOUNDED DEGREEen
dc.subjectCONSTANT FACTOR APPROXIMATIONen
dc.subjectGEOMETRIC PROBLEMSen
dc.subjectGEOMETRIC REPRESENTATIONen
dc.subjectOPTIMIZATION PROBLEMSen
dc.subjectSEMANTIC RELATIONSHIPSen
dc.subjectSEMANTICALLY-RELATED WORDSen
dc.subjectSTRONGLY NP-HARDen
dc.subjectTREES (MATHEMATICS)en
dc.subjectALGORITHMSen
dc.subjectDATA PROCESSINGen
dc.subjectFORESTRYen
dc.subjectINFORMATION RETRIEVALen
dc.subjectPROFITABILITYen
dc.titleSemantic word cloud representations: Hardness and approximation algorithmsen
dc.typeConference Paperen
dc.typeinfo:eu-repo/semantics/conferenceObjecten
dc.typeinfo:eu-repo/semantics/publishedVersionen
dc.identifier.doi10.1007/978-3-642-54423-1_45-
dc.identifier.scopus84899939512-
local.contributor.employeeBarth, L., Institute of Theoretical Informatics, Karlsruhe Institute of Technology, Germany
local.contributor.employeeFabrikant, S.I., Department of Geography, University of Zurich, Switzerland
local.contributor.employeeKobourov, S.G., Department of Computer Science, University of Arizona, United States
local.contributor.employeeLubiw, A., David R. Cheriton School of Computer Science, University of Waterloo, Canada
local.contributor.employeeNöllenburg, M., Institute of Theoretical Informatics, Karlsruhe Institute of Technology, Germany
local.contributor.employeeOkamoto, Y., Dept. Comm. Engineering and Informatics, University of Electro-Communications, Japan
local.contributor.employeePupyrev, S., Department of Computer Science, University of Arizona, United States, Institute of Mathematics and Computer Science, Ural Federal University, Russian Federation
local.contributor.employeeSquarcella, C., Dipartimento di Ingegneria, Roma Tre University, Italy
local.contributor.employeeUeckerdt, T., Department of Mathematics, Karlsruhe Institute of Technology, Germany
local.contributor.employeeWolff, A., Lehrstuhl für Informatik i, Universität Würzburg, Germany
local.description.firstpage514-
local.description.lastpage525-
local.volume8392 LNCS-
dc.identifier.wos000342804300045-
local.contributor.departmentInstitute of Theoretical Informatics, Karlsruhe Institute of Technology, Germany
local.contributor.departmentDepartment of Geography, University of Zurich, Switzerland
local.contributor.departmentDepartment of Computer Science, University of Arizona, United States
local.contributor.departmentDavid R. Cheriton School of Computer Science, University of Waterloo, Canada
local.contributor.departmentDept. Comm. Engineering and Informatics, University of Electro-Communications, Japan
local.contributor.departmentDipartimento di Ingegneria, Roma Tre University, Italy
local.contributor.departmentDepartment of Mathematics, Karlsruhe Institute of Technology, Germany
local.contributor.departmentLehrstuhl für Informatik i, Universität Würzburg, Germany
local.contributor.departmentInstitute of Mathematics and Computer Science, Ural Federal University, Russian Federation
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local.identifier.pure1596653-
local.identifier.eid2-s2.0-84899939512-
local.identifier.wosWOS:000342804300045-
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