Inductive Inference for Large Scale Text Classification: Kernel Approaches and Techniques
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Berlin, Heidelberg
Springer Berlin Heidelberg
2010
|
| Schriftenreihe: | Studies in Computational Intelligence
255 |
| Schlagwörter: | |
| Links: | https://doi.org/10.1007/978-3-642-04533-2 https://doi.org/10.1007/978-3-642-04533-2 https://doi.org/10.1007/978-3-642-04533-2 https://doi.org/10.1007/978-3-642-04533-2 https://doi.org/10.1007/978-3-642-04533-2 |
| Beschreibung: | Text classification is becoming a crucial task to analysts in different areas. In the last few decades, the production of textual documents in digital form has increased exponentially. Their applications range from web pages to scientific documents, including emails, news and books. Despite the widespread use of digital texts, handling them is inherently difficult - the large amount of data necessary to represent them and the subjectivity of classification complicate matters. This book gives a concise view on how to use kernel approaches for inductive inference in large scale text classification; it presents a series of new techniques to enhance, scale and distribute text classification tasks. It is not intended to be a comprehensive survey of the state-of-the-art of the whole field of text classification. Its purpose is less ambitious and more practical: to explain and illustrate some of the important methods used in this field, in particular kernel approaches and techniques |
| Umfang: | 1 Online-Ressource |
| ISBN: | 9783642045332 |
| DOI: | 10.1007/978-3-642-04533-2 |
Internformat
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| 490 | 0 | |a Studies in Computational Intelligence |v 255 | |
| 500 | |a Text classification is becoming a crucial task to analysts in different areas. In the last few decades, the production of textual documents in digital form has increased exponentially. Their applications range from web pages to scientific documents, including emails, news and books. Despite the widespread use of digital texts, handling them is inherently difficult - the large amount of data necessary to represent them and the subjectivity of classification complicate matters. This book gives a concise view on how to use kernel approaches for inductive inference in large scale text classification; it presents a series of new techniques to enhance, scale and distribute text classification tasks. It is not intended to be a comprehensive survey of the state-of-the-art of the whole field of text classification. Its purpose is less ambitious and more practical: to explain and illustrate some of the important methods used in this field, in particular kernel approaches and techniques | ||
| 505 | 0 | |a Fundamentals -- Background on Text Classification -- Kernel Machines for Text Classification -- Approaches and techniques -- Enhancing SVMs for Text Classification -- Scaling RVMs for Text Classification -- Distributing Text Classification in Grid Environments -- Framework for Text Classification | |
| 650 | 4 | |a Engineering | |
| 650 | 4 | |a Artificial intelligence | |
| 650 | 4 | |a Text processing (Computer science | |
| 650 | 4 | |a Computational linguistics | |
| 650 | 4 | |a Engineering mathematics | |
| 650 | 4 | |a Appl.Mathematics/Computational Methods of Engineering | |
| 650 | 4 | |a Document Preparation and Text Processing | |
| 650 | 4 | |a Computational Linguistics | |
| 650 | 4 | |a Artificial Intelligence (incl. Robotics) | |
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Datensatz im Suchindex
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| author | Silva, Catarina |
| author_facet | Silva, Catarina |
| author_role | aut |
| author_sort | Silva, Catarina |
| author_variant | c s cs |
| building | Verbundindex |
| bvnumber | BV041889692 |
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| collection | ZDB-2-ENG |
| contents | Fundamentals -- Background on Text Classification -- Kernel Machines for Text Classification -- Approaches and techniques -- Enhancing SVMs for Text Classification -- Scaling RVMs for Text Classification -- Distributing Text Classification in Grid Environments -- Framework for Text Classification |
| ctrlnum | (OCoLC)699596399 (DE-599)BVBBV041889692 |
| dewey-full | 519 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519 |
| dewey-search | 519 |
| dewey-sort | 3519 |
| dewey-tens | 510 - Mathematics |
| discipline | Informatik Mathematik |
| doi_str_mv | 10.1007/978-3-642-04533-2 |
| format | Electronic eBook |
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| indexdate | 2024-12-20T16:57:06Z |
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| isbn | 9783642045332 |
| language | English |
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| spelling | Silva, Catarina Verfasser aut Inductive Inference for Large Scale Text Classification Kernel Approaches and Techniques by Catarina Silva, Bernardete Ribeiro Berlin, Heidelberg Springer Berlin Heidelberg 2010 1 Online-Ressource txt rdacontent c rdamedia cr rdacarrier Studies in Computational Intelligence 255 Text classification is becoming a crucial task to analysts in different areas. In the last few decades, the production of textual documents in digital form has increased exponentially. Their applications range from web pages to scientific documents, including emails, news and books. Despite the widespread use of digital texts, handling them is inherently difficult - the large amount of data necessary to represent them and the subjectivity of classification complicate matters. This book gives a concise view on how to use kernel approaches for inductive inference in large scale text classification; it presents a series of new techniques to enhance, scale and distribute text classification tasks. It is not intended to be a comprehensive survey of the state-of-the-art of the whole field of text classification. Its purpose is less ambitious and more practical: to explain and illustrate some of the important methods used in this field, in particular kernel approaches and techniques Fundamentals -- Background on Text Classification -- Kernel Machines for Text Classification -- Approaches and techniques -- Enhancing SVMs for Text Classification -- Scaling RVMs for Text Classification -- Distributing Text Classification in Grid Environments -- Framework for Text Classification Engineering Artificial intelligence Text processing (Computer science Computational linguistics Engineering mathematics Appl.Mathematics/Computational Methods of Engineering Document Preparation and Text Processing Computational Linguistics Artificial Intelligence (incl. Robotics) Ingenieurwissenschaften Künstliche Intelligenz Ribeiro, Bernardete Sonstige oth Erscheint auch als Druckausgabe 978-3-642-04532-5 https://doi.org/10.1007/978-3-642-04533-2 Verlag Volltext |
| spellingShingle | Silva, Catarina Inductive Inference for Large Scale Text Classification Kernel Approaches and Techniques Fundamentals -- Background on Text Classification -- Kernel Machines for Text Classification -- Approaches and techniques -- Enhancing SVMs for Text Classification -- Scaling RVMs for Text Classification -- Distributing Text Classification in Grid Environments -- Framework for Text Classification Engineering Artificial intelligence Text processing (Computer science Computational linguistics Engineering mathematics Appl.Mathematics/Computational Methods of Engineering Document Preparation and Text Processing Computational Linguistics Artificial Intelligence (incl. Robotics) Ingenieurwissenschaften Künstliche Intelligenz |
| title | Inductive Inference for Large Scale Text Classification Kernel Approaches and Techniques |
| title_auth | Inductive Inference for Large Scale Text Classification Kernel Approaches and Techniques |
| title_exact_search | Inductive Inference for Large Scale Text Classification Kernel Approaches and Techniques |
| title_full | Inductive Inference for Large Scale Text Classification Kernel Approaches and Techniques by Catarina Silva, Bernardete Ribeiro |
| title_fullStr | Inductive Inference for Large Scale Text Classification Kernel Approaches and Techniques by Catarina Silva, Bernardete Ribeiro |
| title_full_unstemmed | Inductive Inference for Large Scale Text Classification Kernel Approaches and Techniques by Catarina Silva, Bernardete Ribeiro |
| title_short | Inductive Inference for Large Scale Text Classification |
| title_sort | inductive inference for large scale text classification kernel approaches and techniques |
| title_sub | Kernel Approaches and Techniques |
| topic | Engineering Artificial intelligence Text processing (Computer science Computational linguistics Engineering mathematics Appl.Mathematics/Computational Methods of Engineering Document Preparation and Text Processing Computational Linguistics Artificial Intelligence (incl. Robotics) Ingenieurwissenschaften Künstliche Intelligenz |
| topic_facet | Engineering Artificial intelligence Text processing (Computer science Computational linguistics Engineering mathematics Appl.Mathematics/Computational Methods of Engineering Document Preparation and Text Processing Computational Linguistics Artificial Intelligence (incl. Robotics) Ingenieurwissenschaften Künstliche Intelligenz |
| url | https://doi.org/10.1007/978-3-642-04533-2 |
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