Survey of Text Mining: Clustering, Classification, and Retrieval
As the volume of digitized textual information continues to grow, so does the critical need for designing robust and scalable indexing and search strategies/software to meet a variety of user needs. Knowledge extraction or creation from text requires systematic, yet reliable processing that can be c...
Gespeichert in:
Weitere Verfasser: | |
---|---|
Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
New York, NY
Springer New York
2004
|
Ausgabe: | 1st ed. 2004 |
Schlagworte: | |
Online-Zugang: | UBY01 Volltext |
Zusammenfassung: | As the volume of digitized textual information continues to grow, so does the critical need for designing robust and scalable indexing and search strategies/software to meet a variety of user needs. Knowledge extraction or creation from text requires systematic, yet reliable processing that can be codified and adapted for changing needs and environments. Survey of Text Mining is a comprehensive edited survey organized into three parts: Clustering and Classification; Information Extraction and Retrieval; and Trend Detection. Many of the chapters stress the practical application of software and algorithms for current and future needs in text mining. Authors from industry provide their perspectives on current approaches for large-scale text mining and obstacles that will guide R&D activity in this area for the next decade. Topics and features: * Highlights issues such as scalability, robustness, and software tools * Brings together recent research and techniques from academia and industry * Examines algorithmic advances in discriminant analysis, spectral clustering, trend detection, and synonym extraction * Includes case studies in mining Web and customer-support logs for hot- topic extraction and query characterizations * Extensive bibliography of all references, including websites This useful survey volume taps the expertise of academicians and industry professionals to recommend practical approaches to purifying, indexing, and mining textual information. Researchers, practitioners, and professionals involved in information retrieval, computational statistics, and data mining, who need the latest text-mining methods and algorithms, will find the book an indispensable resource |
Beschreibung: | 1 Online-Ressource (XVII, 244 p. 46 illus) |
ISBN: | 9781475743050 |
DOI: | 10.1007/978-1-4757-4305-0 |
Internformat
MARC
LEADER | 00000nmm a2200000zc 4500 | ||
---|---|---|---|
001 | BV047064245 | ||
003 | DE-604 | ||
005 | 00000000000000.0 | ||
007 | cr|uuu---uuuuu | ||
008 | 201216s2004 |||| o||u| ||||||eng d | ||
020 | |a 9781475743050 |9 978-1-4757-4305-0 | ||
024 | 7 | |a 10.1007/978-1-4757-4305-0 |2 doi | |
035 | |a (ZDB-2-SCS)978-1-4757-4305-0 | ||
035 | |a (OCoLC)1227478137 | ||
035 | |a (DE-599)BVBBV047064245 | ||
040 | |a DE-604 |b ger |e aacr | ||
041 | 0 | |a eng | |
049 | |a DE-706 | ||
082 | 0 | |a 006.7 |2 23 | |
084 | |a SK 840 |0 (DE-625)143261: |2 rvk | ||
084 | |a ST 302 |0 (DE-625)143652: |2 rvk | ||
245 | 1 | 0 | |a Survey of Text Mining |b Clustering, Classification, and Retrieval |c edited by Michael W. Berry |
250 | |a 1st ed. 2004 | ||
264 | 1 | |a New York, NY |b Springer New York |c 2004 | |
300 | |a 1 Online-Ressource (XVII, 244 p. 46 illus) | ||
336 | |b txt |2 rdacontent | ||
337 | |b c |2 rdamedia | ||
338 | |b cr |2 rdacarrier | ||
520 | |a As the volume of digitized textual information continues to grow, so does the critical need for designing robust and scalable indexing and search strategies/software to meet a variety of user needs. Knowledge extraction or creation from text requires systematic, yet reliable processing that can be codified and adapted for changing needs and environments. Survey of Text Mining is a comprehensive edited survey organized into three parts: Clustering and Classification; Information Extraction and Retrieval; and Trend Detection. Many of the chapters stress the practical application of software and algorithms for current and future needs in text mining. Authors from industry provide their perspectives on current approaches for large-scale text mining and obstacles that will guide R&D activity in this area for the next decade. Topics and features: * Highlights issues such as scalability, robustness, and software tools * Brings together recent research and techniques from academia and industry * Examines algorithmic advances in discriminant analysis, spectral clustering, trend detection, and synonym extraction * Includes case studies in mining Web and customer-support logs for hot- topic extraction and query characterizations * Extensive bibliography of all references, including websites This useful survey volume taps the expertise of academicians and industry professionals to recommend practical approaches to purifying, indexing, and mining textual information. Researchers, practitioners, and professionals involved in information retrieval, computational statistics, and data mining, who need the latest text-mining methods and algorithms, will find the book an indispensable resource | ||
650 | 4 | |a Multimedia Information Systems | |
650 | 4 | |a Information Storage and Retrieval | |
650 | 4 | |a Information Systems and Communication Service | |
650 | 4 | |a Applications of Mathematics | |
650 | 4 | |a Multimedia information systems | |
650 | 4 | |a Information storage and retrieval | |
650 | 4 | |a Computers | |
650 | 4 | |a Applied mathematics | |
650 | 4 | |a Engineering mathematics | |
650 | 0 | 7 | |a Text Mining |0 (DE-588)4728093-1 |2 gnd |9 rswk-swf |
655 | 7 | |0 (DE-588)1071861417 |a Konferenzschrift |2 gnd-content | |
655 | 7 | |0 (DE-588)4143413-4 |a Aufsatzsammlung |2 gnd-content | |
689 | 0 | 0 | |a Text Mining |0 (DE-588)4728093-1 |D s |
689 | 0 | |5 DE-604 | |
700 | 1 | |a Berry, Michael W. |4 edt | |
776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 9781441930576 |
776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 9780387955636 |
776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 9781475743067 |
856 | 4 | 0 | |u https://doi.org/10.1007/978-1-4757-4305-0 |x Verlag |z URL des Eerstveröffentlichers |3 Volltext |
912 | |a ZDB-2-SCS | ||
940 | 1 | |q ZDB-2-SCS_2000/2004 | |
999 | |a oai:aleph.bib-bvb.de:BVB01-032471357 | ||
966 | e | |u https://doi.org/10.1007/978-1-4757-4305-0 |l UBY01 |p ZDB-2-SCS |q ZDB-2-SCS_2000/2004 |x Verlag |3 Volltext |
Datensatz im Suchindex
_version_ | 1804182062000766976 |
---|---|
adam_txt | |
any_adam_object | |
any_adam_object_boolean | |
author2 | Berry, Michael W. |
author2_role | edt |
author2_variant | m w b mw mwb |
author_facet | Berry, Michael W. |
building | Verbundindex |
bvnumber | BV047064245 |
classification_rvk | SK 840 ST 302 |
collection | ZDB-2-SCS |
ctrlnum | (ZDB-2-SCS)978-1-4757-4305-0 (OCoLC)1227478137 (DE-599)BVBBV047064245 |
dewey-full | 006.7 |
dewey-hundreds | 000 - Computer science, information, general works |
dewey-ones | 006 - Special computer methods |
dewey-raw | 006.7 |
dewey-search | 006.7 |
dewey-sort | 16.7 |
dewey-tens | 000 - Computer science, information, general works |
discipline | Informatik Mathematik |
discipline_str_mv | Informatik Mathematik |
doi_str_mv | 10.1007/978-1-4757-4305-0 |
edition | 1st ed. 2004 |
format | Electronic eBook |
fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03886nmm a2200589zc 4500</leader><controlfield tag="001">BV047064245</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">00000000000000.0</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">201216s2004 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781475743050</subfield><subfield code="9">978-1-4757-4305-0</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/978-1-4757-4305-0</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-2-SCS)978-1-4757-4305-0</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1227478137</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV047064245</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">aacr</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-706</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">006.7</subfield><subfield code="2">23</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">SK 840</subfield><subfield code="0">(DE-625)143261:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ST 302</subfield><subfield code="0">(DE-625)143652:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Survey of Text Mining</subfield><subfield code="b">Clustering, Classification, and Retrieval</subfield><subfield code="c">edited by Michael W. Berry</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">1st ed. 2004</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">New York, NY</subfield><subfield code="b">Springer New York</subfield><subfield code="c">2004</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (XVII, 244 p. 46 illus)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">As the volume of digitized textual information continues to grow, so does the critical need for designing robust and scalable indexing and search strategies/software to meet a variety of user needs. Knowledge extraction or creation from text requires systematic, yet reliable processing that can be codified and adapted for changing needs and environments. Survey of Text Mining is a comprehensive edited survey organized into three parts: Clustering and Classification; Information Extraction and Retrieval; and Trend Detection. Many of the chapters stress the practical application of software and algorithms for current and future needs in text mining. Authors from industry provide their perspectives on current approaches for large-scale text mining and obstacles that will guide R&D activity in this area for the next decade. Topics and features: * Highlights issues such as scalability, robustness, and software tools * Brings together recent research and techniques from academia and industry * Examines algorithmic advances in discriminant analysis, spectral clustering, trend detection, and synonym extraction * Includes case studies in mining Web and customer-support logs for hot- topic extraction and query characterizations * Extensive bibliography of all references, including websites This useful survey volume taps the expertise of academicians and industry professionals to recommend practical approaches to purifying, indexing, and mining textual information. Researchers, practitioners, and professionals involved in information retrieval, computational statistics, and data mining, who need the latest text-mining methods and algorithms, will find the book an indispensable resource</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Multimedia Information Systems</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Information Storage and Retrieval</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Information Systems and Communication Service</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Applications of Mathematics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Multimedia information systems</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Information storage and retrieval</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Computers</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Applied mathematics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Engineering mathematics</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Text Mining</subfield><subfield code="0">(DE-588)4728093-1</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="655" ind1=" " ind2="7"><subfield code="0">(DE-588)1071861417</subfield><subfield code="a">Konferenzschrift</subfield><subfield code="2">gnd-content</subfield></datafield><datafield tag="655" ind1=" " ind2="7"><subfield code="0">(DE-588)4143413-4</subfield><subfield code="a">Aufsatzsammlung</subfield><subfield code="2">gnd-content</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Text Mining</subfield><subfield code="0">(DE-588)4728093-1</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Berry, Michael W.</subfield><subfield code="4">edt</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">9781441930576</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">9780387955636</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">9781475743067</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1007/978-1-4757-4305-0</subfield><subfield code="x">Verlag</subfield><subfield code="z">URL des Eerstveröffentlichers</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-2-SCS</subfield></datafield><datafield tag="940" ind1="1" ind2=" "><subfield code="q">ZDB-2-SCS_2000/2004</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-032471357</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-1-4757-4305-0</subfield><subfield code="l">UBY01</subfield><subfield code="p">ZDB-2-SCS</subfield><subfield code="q">ZDB-2-SCS_2000/2004</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
genre | (DE-588)1071861417 Konferenzschrift gnd-content (DE-588)4143413-4 Aufsatzsammlung gnd-content |
genre_facet | Konferenzschrift Aufsatzsammlung |
id | DE-604.BV047064245 |
illustrated | Not Illustrated |
index_date | 2024-07-03T16:12:22Z |
indexdate | 2024-07-10T09:01:34Z |
institution | BVB |
isbn | 9781475743050 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032471357 |
oclc_num | 1227478137 |
open_access_boolean | |
owner | DE-706 |
owner_facet | DE-706 |
physical | 1 Online-Ressource (XVII, 244 p. 46 illus) |
psigel | ZDB-2-SCS ZDB-2-SCS_2000/2004 ZDB-2-SCS ZDB-2-SCS_2000/2004 |
publishDate | 2004 |
publishDateSearch | 2004 |
publishDateSort | 2004 |
publisher | Springer New York |
record_format | marc |
spelling | Survey of Text Mining Clustering, Classification, and Retrieval edited by Michael W. Berry 1st ed. 2004 New York, NY Springer New York 2004 1 Online-Ressource (XVII, 244 p. 46 illus) txt rdacontent c rdamedia cr rdacarrier As the volume of digitized textual information continues to grow, so does the critical need for designing robust and scalable indexing and search strategies/software to meet a variety of user needs. Knowledge extraction or creation from text requires systematic, yet reliable processing that can be codified and adapted for changing needs and environments. Survey of Text Mining is a comprehensive edited survey organized into three parts: Clustering and Classification; Information Extraction and Retrieval; and Trend Detection. Many of the chapters stress the practical application of software and algorithms for current and future needs in text mining. Authors from industry provide their perspectives on current approaches for large-scale text mining and obstacles that will guide R&D activity in this area for the next decade. Topics and features: * Highlights issues such as scalability, robustness, and software tools * Brings together recent research and techniques from academia and industry * Examines algorithmic advances in discriminant analysis, spectral clustering, trend detection, and synonym extraction * Includes case studies in mining Web and customer-support logs for hot- topic extraction and query characterizations * Extensive bibliography of all references, including websites This useful survey volume taps the expertise of academicians and industry professionals to recommend practical approaches to purifying, indexing, and mining textual information. Researchers, practitioners, and professionals involved in information retrieval, computational statistics, and data mining, who need the latest text-mining methods and algorithms, will find the book an indispensable resource Multimedia Information Systems Information Storage and Retrieval Information Systems and Communication Service Applications of Mathematics Multimedia information systems Information storage and retrieval Computers Applied mathematics Engineering mathematics Text Mining (DE-588)4728093-1 gnd rswk-swf (DE-588)1071861417 Konferenzschrift gnd-content (DE-588)4143413-4 Aufsatzsammlung gnd-content Text Mining (DE-588)4728093-1 s DE-604 Berry, Michael W. edt Erscheint auch als Druck-Ausgabe 9781441930576 Erscheint auch als Druck-Ausgabe 9780387955636 Erscheint auch als Druck-Ausgabe 9781475743067 https://doi.org/10.1007/978-1-4757-4305-0 Verlag URL des Eerstveröffentlichers Volltext |
spellingShingle | Survey of Text Mining Clustering, Classification, and Retrieval Multimedia Information Systems Information Storage and Retrieval Information Systems and Communication Service Applications of Mathematics Multimedia information systems Information storage and retrieval Computers Applied mathematics Engineering mathematics Text Mining (DE-588)4728093-1 gnd |
subject_GND | (DE-588)4728093-1 (DE-588)1071861417 (DE-588)4143413-4 |
title | Survey of Text Mining Clustering, Classification, and Retrieval |
title_auth | Survey of Text Mining Clustering, Classification, and Retrieval |
title_exact_search | Survey of Text Mining Clustering, Classification, and Retrieval |
title_exact_search_txtP | Survey of Text Mining Clustering, Classification, and Retrieval |
title_full | Survey of Text Mining Clustering, Classification, and Retrieval edited by Michael W. Berry |
title_fullStr | Survey of Text Mining Clustering, Classification, and Retrieval edited by Michael W. Berry |
title_full_unstemmed | Survey of Text Mining Clustering, Classification, and Retrieval edited by Michael W. Berry |
title_short | Survey of Text Mining |
title_sort | survey of text mining clustering classification and retrieval |
title_sub | Clustering, Classification, and Retrieval |
topic | Multimedia Information Systems Information Storage and Retrieval Information Systems and Communication Service Applications of Mathematics Multimedia information systems Information storage and retrieval Computers Applied mathematics Engineering mathematics Text Mining (DE-588)4728093-1 gnd |
topic_facet | Multimedia Information Systems Information Storage and Retrieval Information Systems and Communication Service Applications of Mathematics Multimedia information systems Information storage and retrieval Computers Applied mathematics Engineering mathematics Text Mining Konferenzschrift Aufsatzsammlung |
url | https://doi.org/10.1007/978-1-4757-4305-0 |
work_keys_str_mv | AT berrymichaelw surveyoftextminingclusteringclassificationandretrieval |