Text analysis pipelines: Towards ad-hoc large-scale text mining
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Cham
Springer International Publishing
[2015]
|
| Edition: | 1st ed. |
| Series: | Lecture Notes in Computer Science
9383 |
| Subjects: | |
| Online Access: | Volltext Abstract |
| Physical Description: | XX, 302 Seiten Illustrationen |
| ISBN: | 9783319257419 9783319257402 |
| ISSN: | 0302-9743 |
| DOI: | 10.1007/978-3-319-25741-9 |
Staff View
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Record in the Search Index
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| adam_text | TEXT ANALYSIS PIPELINES
/ WACHSMUTH, HENNING
: 2015
ABSTRACT / INHALTSTEXT
THIS MONOGRAPH PROPOSES A COMPREHENSIVE AND FULLY AUTOMATIC APPROACH TO
DESIGNING TEXT ANALYSIS PIPELINES FOR ARBITRARY INFORMATION NEEDS THAT
ARE OPTIMAL IN TERMS OF RUN-TIME EFFICIENCY AND THAT ROBUSTLY MINE
RELEVANT INFORMATION FROM TEXT OF ANY KIND. BASED ON STATE-OF-THE-ART
TECHNIQUES FROM MACHINE LEARNING AND OTHER AREAS OF ARTIFICIAL
INTELLIGENCE, NOVEL PIPELINE CONSTRUCTION AND EXECUTION ALGORITHMS ARE
DEVELOPED AND IMPLEMENTED IN PROTOTYPICAL SOFTWARE. FORMAL ANALYSES OF
THE ALGORITHMS AND EXTENSIVE EMPIRICAL EXPERIMENTS UNDERLINE THAT THE
PROPOSED APPROACH REPRESENTS AN ESSENTIAL STEP TOWARDS THE AD-HOC USE OF
TEXT MINING IN WEB SEARCH AND BIG DATA ANALYTICS. BOTH WEB SEARCH AND
BIG DATA ANALYTICS AIM TO FULFILL PEOPLES’ NEEDS FOR INFORMATION IN AN
ADHOC MANNER. THE INFORMATION SOUGHT FOR IS OFTEN HIDDEN IN LARGE
AMOUNTS OF NATURAL LANGUAGE TEXT. INSTEAD OF SIMPLY RETURNING LINKS TO
POTENTIALLY RELEVANT TEXTS, LEADING SEARCH AND ANALYTICS ENGINES HAVE
STARTED TO DIRECTLY MINE RELEVANT INFORMATION FROM THE TEXTS. TO THIS
END, THEY EXECUTE TEXT ANALYSIS PIPELINES THAT MAY CONSIST OF SEVERAL
COMPLEX INFORMATION-EXTRACTION AND TEXT-CLASSIFICATION STAGES. DUE TO
PRACTICAL REQUIREMENTS OF EFFICIENCY AND ROBUSTNESS, HOWEVER, THE USE OF
TEXT MINING HAS SO FAR BEEN LIMITED TO ANTICIPATED INFORMATION NEEDS
THAT CAN BE FULFILLED WITH RATHER SIMPLE, MANUALLY CONSTRUCTED PIPELINES
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
|
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| doi_str_mv | 10.1007/978-3-319-25741-9 |
| edition | 1st ed. |
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| isbn | 9783319257419 9783319257402 |
| issn | 0302-9743 |
| language | English |
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| series | Lecture Notes in Computer Science |
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| spelling | Wachsmuth, Henning Verfasser aut Text analysis pipelines Towards ad-hoc large-scale text mining by Henning Wachsmuth 1st ed. Cham Springer International Publishing [2015] © 2015 XX, 302 Seiten Illustrationen txt rdacontent c rdamedia cr rdacarrier Lecture Notes in Computer Science 9383 0302-9743 Computer science Computers Mathematical logic Database management Information storage and retrieval Artificial intelligence Computer Science Information Storage and Retrieval Information Systems Applications (incl. Internet) Artificial Intelligence (incl. Robotics) Mathematical Logic and Formal Languages Database Management Computation by Abstract Devices Informatik Künstliche Intelligenz 1\p (DE-588)4113937-9 Hochschulschrift gnd-content Lecture Notes in Computer Science 9383 (DE-604)BV014880109 9383 https://doi.org/10.1007/978-3-319-25741-9 Verlag Volltext Springer Fremddatenuebernahme application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028730281&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Abstract 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Wachsmuth, Henning Text analysis pipelines Towards ad-hoc large-scale text mining Lecture Notes in Computer Science Computer science Computers Mathematical logic Database management Information storage and retrieval Artificial intelligence Computer Science Information Storage and Retrieval Information Systems Applications (incl. Internet) Artificial Intelligence (incl. Robotics) Mathematical Logic and Formal Languages Database Management Computation by Abstract Devices Informatik Künstliche Intelligenz |
| subject_GND | (DE-588)4113937-9 |
| title | Text analysis pipelines Towards ad-hoc large-scale text mining |
| title_auth | Text analysis pipelines Towards ad-hoc large-scale text mining |
| title_exact_search | Text analysis pipelines Towards ad-hoc large-scale text mining |
| title_full | Text analysis pipelines Towards ad-hoc large-scale text mining by Henning Wachsmuth |
| title_fullStr | Text analysis pipelines Towards ad-hoc large-scale text mining by Henning Wachsmuth |
| title_full_unstemmed | Text analysis pipelines Towards ad-hoc large-scale text mining by Henning Wachsmuth |
| title_short | Text analysis pipelines |
| title_sort | text analysis pipelines towards ad hoc large scale text mining |
| title_sub | Towards ad-hoc large-scale text mining |
| topic | Computer science Computers Mathematical logic Database management Information storage and retrieval Artificial intelligence Computer Science Information Storage and Retrieval Information Systems Applications (incl. Internet) Artificial Intelligence (incl. Robotics) Mathematical Logic and Formal Languages Database Management Computation by Abstract Devices Informatik Künstliche Intelligenz |
| topic_facet | Computer science Computers Mathematical logic Database management Information storage and retrieval Artificial intelligence Computer Science Information Storage and Retrieval Information Systems Applications (incl. Internet) Artificial Intelligence (incl. Robotics) Mathematical Logic and Formal Languages Database Management Computation by Abstract Devices Informatik Künstliche Intelligenz Hochschulschrift |
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| volume_link | (DE-604)BV014880109 |
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