000 03606nam a22005895i 4500
001 978-3-319-91815-0
003 DE-He213
005 20220801220918.0
007 cr nn 008mamaa
008 180607s2019 sz | s |||| 0|eng d
020 _a9783319918150
_9978-3-319-91815-0
024 7 _a10.1007/978-3-319-91815-0
_2doi
050 4 _aTK5101-5105.9
072 7 _aTJK
_2bicssc
072 7 _aTEC041000
_2bisacsh
072 7 _aTJK
_2thema
082 0 4 _a621.382
_223
100 1 _aJo, Taeho.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_953069
245 1 0 _aText Mining
_h[electronic resource] :
_bConcepts, Implementation, and Big Data Challenge /
_cby Taeho Jo.
250 _a1st ed. 2019.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2019.
300 _aXIII, 373 p. 236 illus., 148 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Big Data,
_x2197-6511 ;
_v45
505 0 _aPart I: Foundation -- Introduction -- Text Indexing -- Text Encoding -- Text Association -- Part II: Text Categorization -- Text Categorization: Conceptual View -- Text Categorization: Approaches -- Text Categorization: Implementation -- Text Categorization: Evaluation -- Part III: Text Clustering -- Text Clustering: Conceptual View -- Text Clustering: Approaches -- Text Clustering: Implementation -- Text Clustering: Evaluation -- Part IV: Advanced Topics -- Text Summarization -- Text Segmentation -- Taxonomy Generation -- Dynamic Document Organization -- References -- Index.
520 _aThis book discusses text mining and different ways this type of data mining can be used to find implicit knowledge from text collections. The author provides the guidelines for implementing text mining systems in Java, as well as concepts and approaches. The book starts by providing detailed text preprocessing techniques and then goes on to provide concepts, the techniques, the implementation, and the evaluation of text categorization. It then goes into more advanced topics including text summarization, text segmentation, topic mapping, and automatic text management. Presents techniques of preprocessing texts into structured forms; Outlines concepts of text categorization and clustering, their algorithms, and implementation guides; Includes advanced topics such as text summarization, text segmentation, topic mapping, and automatic text management.
650 0 _aTelecommunication.
_910437
650 0 _aComputational intelligence.
_97716
650 0 _aData mining.
_93907
650 0 _aInformation storage and retrieval systems.
_922213
650 0 _aQuantitative research.
_94633
650 1 4 _aCommunications Engineering, Networks.
_931570
650 2 4 _aComputational Intelligence.
_97716
650 2 4 _aData Mining and Knowledge Discovery.
_953070
650 2 4 _aInformation Storage and Retrieval.
_923927
650 2 4 _aData Analysis and Big Data.
_953071
710 2 _aSpringerLink (Online service)
_953072
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319918143
776 0 8 _iPrinted edition:
_z9783319918167
776 0 8 _iPrinted edition:
_z9783030063023
830 0 _aStudies in Big Data,
_x2197-6511 ;
_v45
_953073
856 4 0 _uhttps://doi.org/10.1007/978-3-319-91815-0
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c79078
_d79078