skip to content
Machine learning for text Preview this item
ClosePreview this item
Checking...

Machine learning for text

Author: Charu C Aggarwal
Publisher: Cham, Switzerland : Springer, 2018.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
Text analytics is a field that lies on the interface of information retrieval, machine learning, and natural language processing. This book carefully covers a coherently organized framework drawn from these intersecting topics. The chapters of this book span three broad categories: 1. Basic algorithms: Chapters 1 through 8 discuss the classical algorithms for text analytics such as preprocessing, similarity  Read more...
Rating:

(not yet rated) 0 with reviews - Be the first.

Subjects
More like this

Find a copy in the library

&AllPage.SpinnerRetrieving; Finding libraries that hold this item...

Details

Genre/Form: Electronic books
Additional Physical Format: Printed edition:
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Charu C Aggarwal
ISBN: 9783319735313 3319735314
OCLC Number: 1029870455
Description: 1 online resource (xxiii, 493 pages) : illustrations (some color)
Contents: 1 An Introduction to Text Analytics --
2 Text Preparation and Similarity Computation --
3 Matrix Factorization and Topic Modeling --
4 Text Clustering --
5 Text Classification: Basic Models --
6 Linear Models for Classification and Regression --
7 Classifier Performance and Evaluation --
8 Joint Text Mining with Heterogeneous Data --
9 Information Retrieval and Search Engines --
10 Text Sequence Modeling and Deep Learning --
11 Text Summarization --
12 Information Extraction --
13 Opinion Mining and Sentiment Analysis --
14 Text Segmentation and Event Detection.
Responsibility: Charu C. Aggarwal.

Abstract:

Text analytics is a field that lies on the interface of information retrieval, machine learning, and natural language processing. This book carefully covers a coherently organized framework drawn from these intersecting topics. The chapters of this book span three broad categories: 1. Basic algorithms: Chapters 1 through 8 discuss the classical algorithms for text analytics such as preprocessing, similarity computation, topic modeling, matrix factorization, clustering, classification, regression, and ensemble analysis. 2. Domain-sensitive learning: Chapters 8 and 9 discuss learning models in heterogeneous settings such as a combination of text with multimedia or Web links. The problem of information retrieval and Web search is also discussed in the context of its relationship with ranking and machine learning methods. 3. Sequence-centric mining: Chapters 10 through 14 discuss various sequence-centric and natural language applications, such as feature engineering, neural language models, deep learning, text summarization, information extraction, opinion mining, text segmentation, and event detection. This book covers text analytics and machine learning topics from the simple to the advanced. Since the coverage is extensive, multiple courses can be offered from the same book, depending on course level.

Reviews

Editorial reviews

Publisher Synopsis

"The book discusses many key technologies used today in social media, such as opinion mining or event detection. One of the most promising new technologies, deep learning, is discussed as well. This Read more...

 
User-contributed reviews
Retrieving GoodReads reviews...
Retrieving DOGObooks reviews...

Tags

Be the first.
Confirm this request

You may have already requested this item. Please select Ok if you would like to proceed with this request anyway.

Linked Data


Primary Entity

<http://www.worldcat.org/oclc/1029870455> # Machine learning for text
    a schema:CreativeWork, schema:Book, schema:MediaObject ;
    library:oclcnum "1029870455" ;
    library:placeOfPublication <http://id.loc.gov/vocabulary/countries/sz> ;
    schema:about <http://experiment.worldcat.org/entity/work/data/4657365351#Topic/artificial_intelligence> ; # Artificial intelligence
    schema:about <http://experiment.worldcat.org/entity/work/data/4657365351#Topic/machine_learning> ; # Machine learning
    schema:about <http://experiment.worldcat.org/entity/work/data/4657365351#Topic/text_processing_computer_science> ; # Text processing (Computer science)
    schema:about <http://experiment.worldcat.org/entity/work/data/4657365351#Topic/data_mining> ; # Data mining
    schema:about <http://dewey.info/class/006.31/e23/> ;
    schema:about <http://experiment.worldcat.org/entity/work/data/4657365351#Topic/computers_intelligence_ai_&_semantics> ; # Computers--Intelligence (AI) & Semantics
    schema:about <http://experiment.worldcat.org/entity/work/data/4657365351#Topic/computers_database_management_data_mining> ; # Computers--Database Management--Data Mining
    schema:author <http://experiment.worldcat.org/entity/work/data/4657365351#Person/aggarwal_charu_c> ; # Charu C. Aggarwal
    schema:bookFormat schema:EBook ;
    schema:datePublished "2018" ;
    schema:description "Text analytics is a field that lies on the interface of information retrieval, machine learning, and natural language processing. This book carefully covers a coherently organized framework drawn from these intersecting topics. The chapters of this book span three broad categories: 1. Basic algorithms: Chapters 1 through 8 discuss the classical algorithms for text analytics such as preprocessing, similarity computation, topic modeling, matrix factorization, clustering, classification, regression, and ensemble analysis. 2. Domain-sensitive learning: Chapters 8 and 9 discuss learning models in heterogeneous settings such as a combination of text with multimedia or Web links. The problem of information retrieval and Web search is also discussed in the context of its relationship with ranking and machine learning methods. 3. Sequence-centric mining: Chapters 10 through 14 discuss various sequence-centric and natural language applications, such as feature engineering, neural language models, deep learning, text summarization, information extraction, opinion mining, text segmentation, and event detection. This book covers text analytics and machine learning topics from the simple to the advanced. Since the coverage is extensive, multiple courses can be offered from the same book, depending on course level."@en ;
    schema:description "1 An Introduction to Text Analytics -- 2 Text Preparation and Similarity Computation -- 3 Matrix Factorization and Topic Modeling -- 4 Text Clustering -- 5 Text Classification: Basic Models -- 6 Linear Models for Classification and Regression -- 7 Classifier Performance and Evaluation -- 8 Joint Text Mining with Heterogeneous Data -- 9 Information Retrieval and Search Engines -- 10 Text Sequence Modeling and Deep Learning -- 11 Text Summarization -- 12 Information Extraction -- 13 Opinion Mining and Sentiment Analysis -- 14 Text Segmentation and Event Detection."@en ;
    schema:exampleOfWork <http://worldcat.org/entity/work/id/4657365351> ;
    schema:genre "Electronic books"@en ;
    schema:inLanguage "en" ;
    schema:isSimilarTo <http://worldcat.org/entity/work/data/4657365351#CreativeWork/> ;
    schema:name "Machine learning for text"@en ;
    schema:productID "1029870455" ;
    schema:url <https://link.springer.com/book/10.1007/978-3-319-73531-3> ;
    schema:url <https://link.springer.com/book/10.1007/978-3-319-73530-6> ;
    schema:url <http://VH7QX3XE2P.search.serialssolutions.com/?V=1.0&L=VH7QX3XE2P&S=JCs&C=TC0001986947&T=marc&tab=BOOKS> ;
    schema:url <https://public.ebookcentral.proquest.com/choice/publicfullrecord.aspx?p=5589130> ;
    schema:url <https://doi.org/10.1007/978-3-319-73531-3> ;
    schema:workExample <http://dx.doi.org/10.1007/978-3-319-73531-3> ;
    schema:workExample <http://worldcat.org/isbn/9783319735313> ;
    umbel:isLike <http://bnb.data.bl.uk/id/resource/GBB8N8778> ;
    wdrs:describedby <http://www.worldcat.org/title/-/oclc/1029870455> ;
    .


Related Entities

<http://experiment.worldcat.org/entity/work/data/4657365351#Person/aggarwal_charu_c> # Charu C. Aggarwal
    a schema:Person ;
    schema:familyName "Aggarwal" ;
    schema:givenName "Charu C." ;
    schema:name "Charu C. Aggarwal" ;
    .

<http://experiment.worldcat.org/entity/work/data/4657365351#Topic/artificial_intelligence> # Artificial intelligence
    a schema:Intangible ;
    schema:name "Artificial intelligence"@en ;
    .

<http://experiment.worldcat.org/entity/work/data/4657365351#Topic/computers_database_management_data_mining> # Computers--Database Management--Data Mining
    a schema:Intangible ;
    schema:name "Computers--Database Management--Data Mining"@en ;
    .

<http://experiment.worldcat.org/entity/work/data/4657365351#Topic/computers_intelligence_ai_&_semantics> # Computers--Intelligence (AI) & Semantics
    a schema:Intangible ;
    schema:name "Computers--Intelligence (AI) & Semantics"@en ;
    .

<http://experiment.worldcat.org/entity/work/data/4657365351#Topic/text_processing_computer_science> # Text processing (Computer science)
    a schema:Intangible ;
    schema:name "Text processing (Computer science)"@en ;
    .

<http://worldcat.org/isbn/9783319735313>
    a schema:ProductModel ;
    schema:isbn "3319735314" ;
    schema:isbn "9783319735313" ;
    .


Content-negotiable representations

Close Window

Please sign in to WorldCat 

Don't have an account? You can easily create a free account.