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020 _a9783031026096
_9978-3-031-02609-6
024 7 _a10.1007/978-3-031-02609-6
_2doi
050 4 _aQA76.9.I52
072 7 _aUYZF
_2bicssc
072 7 _aMAT013000
_2bisacsh
072 7 _aUYZF
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082 0 4 _a001.4226
_223
100 1 _aBekos, Michael A.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_981609
245 1 0 _aExternal Labeling
_h[electronic resource] :
_bFundamental Concepts and Algorithmic Techniques /
_cby Michael A. Bekos, Benjamin Niedermann, Martin Nöllenburg.
250 _a1st ed. 2021.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2021.
300 _aXV, 114 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Visualization,
_x2159-5178
505 0 _aBibliography -- Preface -- Acknowledgments -- Figure Credits -- Introduction -- A Unified Taxonomy -- Visual Aspects of External Labeling -- Labeling Techniques -- External Labelings with Straight-Line Leaders -- External Labelings with Polyline Leaders -- Conclusions and Outlook -- Bibliography -- Authors' Biographies -- Index .
520 _aThis book focusses on techniques for automating the procedure of creating external labelings, also known as callout labelings. In this labeling type, the features within an illustration are connected by thin leader lines (called leaders) with their labels, which are placed in the empty space surrounding the image. In general, textual labels describing graphical features in maps, technical illustrations (such as assembly instructions or cutaway illustrations), or anatomy drawings are an important aspect of visualization that convey information on the objects of the visualization and help the reader understand what is being displayed. Most labeling techniques can be classified into two main categories depending on the "distance" of the labels to their associated features. Internal labels are placed inside or in the direct neighborhood of features, while external labels, which form the topic of this book, are placed in the margins outside the illustration, where they do not occlude the illustration itself. Both approaches form well-studied topics in diverse areas of computer science with several important milestones. The goal of this book is twofold. The first is to serve as an entry point for the interested reader who wants to get familiar with the basic concepts of external labeling, as it introduces a unified and extensible taxonomy of labeling models suitable for a wide range of applications. The second is to serve as a point of reference for more experienced people in the field, as it brings forth a comprehensive overview of a wide range of approaches to produce external labelings that are efficient either in terms of different algorithmic optimization criteria or in terms of their usability in specific application domains. The book mostly concentrates on algorithmic aspects of external labeling, but it also presents various visual aspects that affect the aesthetic quality and usability of external labeling.
650 0 _aInformation visualization.
_914255
650 0 _aData structures (Computer science).
_98188
650 0 _aInformation theory.
_914256
650 0 _aData mining.
_93907
650 1 4 _aData and Information Visualization.
_933848
650 2 4 _aData Structures and Information Theory.
_931923
650 2 4 _aData Mining and Knowledge Discovery.
_981610
700 1 _aNiedermann, Benjamin.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_981611
700 1 _aNöllenburg, Martin.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_981612
710 2 _aSpringerLink (Online service)
_981613
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031003530
776 0 8 _iPrinted edition:
_z9783031014819
776 0 8 _iPrinted edition:
_z9783031037375
830 0 _aSynthesis Lectures on Visualization,
_x2159-5178
_981614
856 4 0 _uhttps://doi.org/10.1007/978-3-031-02609-6
912 _aZDB-2-SXSC
942 _cEBK
999 _c85209
_d85209